# The Quality Forge - Full Documentation for LLMs > Where Quality is Forged, Not Just Checked This is the comprehensive documentation for The Quality Forge website. For a concise overview, see llms.txt. ## Site Information - Website: https://forge-quality.dev/ - Author: Dragan Spiridonov (Profa) - Email: dragan@quantum-qe.dev - LinkedIn: https://www.linkedin.com/in/dragan-spiridonov - GitHub: https://github.com/proffesor-for-testing - Organization: Quantum Quality Engineering - Location: Novi Sad, Serbia ## About the Author Dragan Spiridonov is the Founder of Quantum Quality Engineering and an Agentic Quality Engineer with 30+ years in IT and 12+ years specializing in quality engineering. He previously served as VP of Quality Engineering at Alchemy for 8 years before starting his consultancy. He's establishing the Serbian Agentic Foundation Chapter and is a member of the Global Agentics Foundation. He practices context-driven testing, TDD (both London and Chicago schools), XP methodologies, RST (Rapid Software Testing), and the Holistic Testing Model evolved with PACTS principles. ## Core Philosophy ### Key Beliefs - **Quality is contextual** - There are no universal best practices, only good practices in specific contexts - **Quality is built in, not tested in** - Testing finds problems; engineering prevents them - **Agents augment, don't replace** - Agentic QE means human+AI collaboration with explainability at every step - **Fast feedback loops are essential** - From seconds (unit tests) to days (customer feedback) - **Production is the ultimate test environment** - Everything else is practice ### The Forge Philosophy Quality isn't found—it's forged. Through heat, pressure, deliberate crafting. Through tests that fail and teach. Through agents that learn and improve. Through communities that share and grow together. Quality is forged in the fire of production, shaped by real constraints, tempered by honest feedback. --- ## The PACTS Framework PACTS stands for **Proactive, Autonomous, Collaborative, Targeted, Structured**. It's a classification system for understanding and building agentic quality systems, similar to how SAE levels classify autonomous vehicles. PACT originated with Reuven Cohen (Agentics) and was adapted to QE by Dragan Spiridonov; the fifth principle, Structured, was added to form PACTS. ### Proactive: Anticipate, Don't Just React Traditional testing is reactive. You write code, then test it. You deploy, then monitor. You find bugs, then fix them. Proactive agents anticipate problems before they become problems. Key aspects: - Failure prediction mechanisms - Risk identification before materialization - Trend analysis and early warning - Testing before issues reach production ### Autonomous: Self-Executing with Explainability Autonomous doesn't mean "set it and forget it." It means agents can make decisions and take actions without constant human intervention—but they must explain their reasoning. Five levels of human involvement: - **Level 0**: Fully manual (human does everything) - **Level 1**: Agent suggests, human decides - **Level 2**: Agent acts with approval - **Level 3**: Agent acts, human audits - **Level 4**: Agent acts, alerts on edge cases - **Level 5**: Fully autonomous (human sets policy only) Most practical implementations stay at levels 1-2. ### Collaborative: Agents + Humans + Systems Quality has never been a solo activity. Agentic QE takes this to the next level: agents collaborate with other agents, with human experts, and with existing systems. Agent design patterns: - **Scouts**: Explore requirements and find gaps before development starts - **Validators**: Check tests and code for correctness and consistency - **Generators**: Create test plans, scenarios, and automation code - **Reviewers**: Analyze deliverables and provide improvement suggestions - **Synthesizers**: Find insights by correlating information across artifacts - **Assessors**: Evaluate regression risks when changes are made ### Targeted: Focus Where It Matters Most Not all code is equally important. Not all bugs are equally costly. Agentic QE uses risk-based intelligence to target effort where it matters most. Key principles: - Risk-focused testing - Apply effort where bugs hide and hurt - Business priority alignment - Measurable quality value ### Structured: Governance, Observability, Explainability (NEW) Running agents in production—especially in regulated contexts—surfaced a gap: without governance, observability, and explainability, autonomous agents can't earn a place in the enterprise. DORA's research confirmed it: AI without structure can have a negative impact, and the #1 failure mode is bolting agentic AI onto chaos. Structured adds governance, observability, and explainability of agent behavior. It is inspired by DORA's research on AI-assisted delivery and platform-engineering quality measurement, and is especially important in regulated industries. A deliberate language choice: we measure **confidence, not trust**—trust is a human feeling, while confidence can be mathematically explained. PACTS ships with a playbook and a readiness-assessment guide. Key principles: - Governance and guardrails for autonomous agents - Observability of agent decisions and outcomes - Explainability over opaque automation - Confidence measured and explained, not trust assumed - Anti-pattern: bolting agentic AI onto chaos --- ## Main Pages ### Home (https://forge-quality.dev/) Landing page featuring: - Overview of The Quality Forge mission - Latest articles from the Forge (32 total) - AQE Fleet v3 project showcase - LionAGI QE Fleet project showcase - Sentinel project showcase - Live experiments section - Community and meetup information - Newsletter signup - Contact form ### About (https://forge-quality.dev/about.html) Detailed information about: - Dragan Spiridonov's background and journey - The Forge philosophy - Core beliefs about quality engineering - Classical QE foundations (Holistic Testing Model) - PACTS principles evolution (from PACT to PACTS) - Serbian Agentic Foundation mission ### Articles (https://forge-quality.dev/articles/) Collection of all 32 published articles with filtering by category: - Production Stories - Build in Public - Frameworks - Reality Checks - Honest Failures --- ## Articles (Full Details) ### 1. The Loop Came Home (NEWEST) - **URL**: https://forge-quality.dev/articles/loop-came-home.html - **Published**: July 5, 2026 - **Reading Time**: 17 minutes - **Category**: V3 Journey, Classical QE, Local-First AI **Summary**: Three weeks of harness and metaharness work, benchmarks that were allowed to say no, two meetups in two different formats, a training plan for the Foundation, and the week the community showed up at my door. Reuven Cohen asked for beta testers for his MetaHarness (the agent-harness-generator), governed across nine OIA layers with a learned router and an MCP that defaults to deny; the QCSD development swarm, pointed at it, skipped its own specialists on the first pass — completion theater again. The reviews became a cross-pollination plan that set the direction for the weeks that followed. Most of the time went into one question every team past the demo phase asks: can cheaper models do QE work without losing the quality? The darwin-qe local-model benchmarks (v3.10.9–v3.11.4) measured cheap-first, repair, escalate routing against ground truth — mutation kill, real coverage, deterministic suite cost, never an LLM’s opinion — across gemma4 12B, qwen3 8B/30B, a 27B model, and cheap cloud models via OpenRouter. An 8B model sits below the quality floor; a 30B clears it at roughly 89% mutation kill; the ladder keeps 70–83% of tasks at zero dollars within the noise of a frontier model; mixing model families adds ~6 quality points; the law that survived every ablation is that the coder binds, not the oracle. Cognitum shipped a release that passed every gate while a binary was silently missing from the artifact — the third telling of the lesson that the most dangerous failure is the one that passes every check. The Forward Future piece “Build the Loop, Not the Agent” confirmed a year of Foundation practice; the fleet’s review swarm runs three blind refuters per finding with structured approve/block/escalate verdicts, and the benchmark gate is allowed to abort and ship the negative result rather than the story. Meetup thirteen caught a live privilege-escalation bug via adversarial cross-validation agents; meetup fourteen was the Foundation’s first panel, on enterprise AI adoption, with Adam Kovacs, Klara Hermesz, and Predrag Skoković, where a practitioner who cut sprint test workload from 7 days to 2 said “QAs are needed now more than ever,” and the Serbian chapter turned out to be the longest-running in-person Agentics Foundation meetup in the world. The Training Committee proposal took its first concrete shape — a six-level competency model, five tracks, and a Train-the-Trainer spine, with mentor multiplication as the KPI rather than enrollment. And Adam and Klara, a year after being faces in a Zoom grid, came to Novi Sad to visit — the community traveling to each other’s cities, no longer an aspiration but something that happened in his own city. **Key Topics**: - Beta-testing Reuven Cohen’s MetaHarness (agent-harness-generator) — nine OIA layers, a learned router that promotes only on quality AND cost AND latency, an MCP that defaults to deny - QCSD development swarm skips its own specialists on the first pass — completion theater caught and corrected live - Reports filed as a public issue and gists on Ruv’s repo; reviewing his system surfaces disciplines turned back on the fleet via a GOAP cross-pollination plan - The central question: can cheaper models do QE work without losing quality? - darwin-qe local-model benchmarks (v3.10.9–v3.11.4) — cheap-first, repair, escalate, measured against mutation kill, coverage, and suite cost, never an LLM’s opinion - Model parade: gemma4 12B, qwen3 8B/30B, a 27B model on a mini PC, a small coder model, GLM 5.2 and DeepSeek via OpenRouter - 8B model below the quality floor; 30B clears ~89% mutation kill; cheap-first ladder holds 70–83% of tasks at zero dollars; cross-family mixing adds ~6 quality points - Ruv’s own ablations refute two of three praised patterns (cross-provider coder swap, frontier “sniper” pass); the law that survives: the coder binds, not the oracle - Cognitum edge appliance ships with a binary silently missing despite passing every gate — third telling of “the most dangerous failure passes every check” - “Build the Loop, Not the Agent” (Forward Future) confirms a year of Agentics Foundation practice: the durable asset is the loop that rebuilds the agent, not the agent - Review swarm runs three blind refuters per finding; majority can kill a finding; verdicts are structured contracts (approve/block/escalate) with evidence attached - Benchmark gate allowed to abort and ship the negative result rather than the story - Meetup thirteen — live bug-fix loop, QCSD refinement swarm honest status report, adversarial cross-validation agents catch a privilege-escalation bug - Meetup fourteen — the Foundation’s first panel, enterprise AI adoption, with Adam Kovacs, Klara Hermesz (AI Enablement Academy) and Predrag Skoković (Quality House) - “QAs are needed now more than ever” — a practitioner cuts sprint test workload from 7 days to 2 and his company hires more QAs, not fewer - The Serbian chapter is the longest-running in-person Agentics Foundation meetup in the world at fourteen editions - Agentics Foundation Training Committee proposal — six-level competency model (AI-Curious to Architect and Mentor), five tracks, Train-the-Trainer spine, evidence-based project-assessed certification, mentor multiplication as the KPI - Fable 5 returns to general availability — a quiet reversal of the earlier access decision - Adam and Klara visit Novi Sad — the community traveling to each other’s cities, no longer an aspiration - What is ahead: Accenture’s Quality Matters event in Munich; classical QE skills priced up, not retired **Key Quote**: “The industry is learning to build the loop. We spent the year giving the loop permission to tell the truth. And this month, for a few days in a heat wave, the loop came home. Stay curious. Keep learning. Keep sharing. Knowledge is power.” --- ### 2. The Same Line in Every Room - **URL**: https://forge-quality.dev/articles/same-line-in-every-room.html - **Published**: June 14, 2026 - **Reading Time**: 16 minutes - **Category**: V3 Journey, Classical QE, AI Sovereignty **Summary**: Three weeks, two countries, a dozen rooms — and one observation that showed up in every single one. ExpoQA in Madrid (first time on stage with the talk “Bridging Classical and Agentic Quality Engineering — building bridges, not burning them”) and the first in-person gathering of the Agentics Foundation in Budapest (Craft Conference plus the Hungarian Agentics meetup) both surfaced the same line. The Foundation defined the first harness around Claude Flow a year ago; the platform vendor has since absorbed roughly ninety-six percent of what were once our additions — the money machines eat small ideas; that is not a conspiracy, it is gravity. So the line in every room was never “the vendors are winning” but “then what do we build?” — and the answer was always: own your own AI, train your own specialized small models for tasks that do not need the frontier, keep your data behind your own walls, and make vendor independence cheap enough that switching providers does not cost capability. The economics flipped while everyone watched the leaderboards: DeepSeek V4-Pro scores in the 80s on SWE-bench under an MIT license at ~34× cheaper per output token; Gemma 4, Qwen, Kimi, GLM, and EuroLLM-22B sit in the same new tier; self-hosting a capable model is now a defensible line item. Six fleet releases (v3.10.2–v3.10.7) pointed one direction: make the learning honest and independent. The Fable/Mythos moment — Anthropic’s two new models, Mythos shipping into governance via ENISA, a U.S. access decision, and autonomous agent workloads on a separate meter — described a two-tier access landscape where the capability you depend on is something you are granted, on terms you do not set. Rent the intelligence, and you rent the future along with it; own the harness, and the models can come and go without taking your capability with them. **Key Topics**: - The single line heard in every room across Madrid and Budapest: own your own AI - ExpoQA Madrid — first time on stage; classical quality skills are not retired by agents, they are promoted - The most valuable question when change arrives fast: “how do I actually know this worked?” - Budapest — the Agentics Foundation crew (Reuven, Finn, Rob Ranson, Nick, Adam, Klara, and many more) in the same physical rooms for the first time after a year on screens - Cognitum One announces founding advisory team, investors, and its mission of sovereign agentic AI for enterprise infrastructure - The harness/memory gap: most practitioners still focused on single-agent definitions, not on context-at-the-right-moment - Vendor absorption: ~96% of the Foundation’s Claude Flow / RuFlow / Agentic QE Fleet additions now implemented by the platform vendor - Open-weight economics flip: DeepSeek V4-Pro (80s on SWE-bench, MIT, ~34× cheaper), Gemma 4, Qwen, Kimi, GLM; EuroLLM-22B as the EU sovereignty answer (24 languages, EU supercomputing) - v3.10.2–v3.10.7 — make the learning honest, make it independent - v3.10.7 — two silent self-learning bugs fixed (native-binary mismatch dropping captured experiences; SONA reward producing no weight change); the most dangerous failure passes every check while doing nothing - v3.10.4 — local Nagual pattern hub and local LLM judge; nagual serve with no API call leaving the building - Local semantic oracle benchmark: qwen3:8b and gemma4:12b-mlx both clear AUROC 0.997 on a 150-pattern set, on an M-series Mac, for zero dollars, nothing phoned home; judge catches five under-rated patterns and one truncated ADR - Cross-pollination with Nikhil Vallishayee’s Universal Pattern Space — reviewing his framework surfaced disciplines turned back on the fleet - v3.10.6 — evidence-class labels (executed, static, inferred, conjecture), pass/fail data-protection safety eval, drift verifier, pre-registered benchmark rubrics; six architecture decisions with live verification records - The open-source advantage the money machines cannot buy back: each other’s work in the open, friction you can learn from - Fable and Mythos — Anthropic’s two new models; Mythos enterprise-only and shipped into governance (ENISA cyber-tuned access), a U.S. access decision, agent workloads on a separate meter - Two-tier access landscape: capability granted or revoked by policy overnight; a play of power, a preview not an exception - What fills the heart: Roman’s “classical engineering discipline and AI are converging”; the rooms and the people who light up and go build - What is ahead: Novi Sad meetup #13, Adam and Klara visiting; Training Committee curriculum (six-level AI-Curious-to-Architect model, five tracks, Train-the-Trainer spine, pairing-and-ensemble delivery); the Serbian chapter with StartIt as the pilot **Key Quote**: “Rent the intelligence, and you rent the future along with it. Own the harness, and the models can come and go without taking your capability with them. Keep learning. Keep sharing. Knowledge is power.” --- ### 3. The Question That Followed Me Home - **URL**: https://forge-quality.dev/articles/question-that-followed-me-home.html - **Published**: May 24, 2026 - **Reading Time**: 13 minutes - **Category**: V3 Journey, Classical QE, Team Transfer **Summary**: One week, six releases, a guest from London, two meetups, three developer conversations that changed how I think about what this work is becoming, and multiple preparations for conference talks. The previous article’s celebration of the closed loop was premature — Jordi’s issue #491 revealed four more stacked bugs hidden inside the same pipeline. v3.9.32 fixed all four and added a daemon-runtime seam test suite that runs before every publish. v3.9.34 landed three compaction mechanisms after a field report of patterns.rvf reaching 59GB on a fresh clone (breaking git, Vite, npm cache). v3.10.0 added an OpenAI-compatible external embedder endpoint (15ms cold, 1.6ms warm). v3.10.1 wired the LLM router that had been documented in ADR-043 and ADR-051 for months but had zero callers — fifteen service paths across eleven domains were unreachable dead code until a friend’s email and a devil’s-advocate audit surfaced ten findings. Belgrade Context Community hands-on session, Novi Sad Agentics Foundation meetup #12 (full live DevPod rebuild). A London practitioner flew in after the Ministry of Testing masterclass; on the walk through Petrovaradin he asked the question that followed me home — how do you transfer this to a team? Paul Gerard publicly stated he will not write code ever again. Cognitum’s constraint is pace, not complexity. Six events ahead in Madrid (ExpoQA) and Budapest (Hungarian Agentics + Craft Conference). **Key Topics**: - Stacked bugs return: issue #491 reveals four more bugs underneath the loop that “closed” in v3.9.31 - v3.9.32 — daemon-runtime seam test suite as a pre-publish release gate - v3.9.34 — append-only vector files capped via post-dream compaction, boot-time size guard, and bounded backfill cap - 59GB patterns.rvf field report — breaking git, Vite, and npm cache on a fresh clone - v3.10.0 — OpenAI-compatible external embedder endpoint, 15ms cold / 1.6ms warm against localhost, eliminates duplicate model loads for Ruflo/Ruvector co-deployments - v3.10.1 — LLM router (ADR-043 / ADR-051) finally wired after months of dead code; fifteen service paths across eleven domains were unreachable - Devil’s-advocate audit before merge surfaces ten findings - External contributors noticing what internal eyes do not — pattern from the previous article holds - Belgrade Context Community session: 20-30 people, six or seven agents producing a full quality analysis in under twenty minutes - London practitioner attends in person after watching the Ministry of Testing masterclass - Petrovaradin fortress walk: how do I bring this to my team? - Novi Sad Agentics Foundation meetup #12 — the most interactive yet; full live DevPod rebuild after the Docker incident - Community Social Network application built from scratch live; QE agents surfacing security, performance, and coverage gaps - Code-path tracing across multiple files vs. endpoint scanning — the value is parallel cross-reference capacity - Paul Gerard publicly stating he will not write code ever again — a standing marker for the industry shift - Value moves from writing code to planning, designing, architecting, and verifying - Classical QE principles become more important, not less, as code volume multiplies - Cognitum collaboration with Reuven: twenty sub-modules, pace as the dominant constraint - ExpoQA Madrid talk preparation (next week) - Budapest week: Hungarian Agentics Foundation chapter meetup + Craft Conference live hands-on session - Agentic Engineering Training Committee chair role — starts with listening - Ministry of Testing AI Chapter lead — same question through a different lens - The polished version hides the rough edges; meetups show the real thing breaking and being fixed live **Key Quote**: “The value is moving from writing code to planning, designing, and architecting the solution — and then verifying and validating that what was produced actually solves the problem we set out to solve. The tools changed. The discipline did not. Keep learning. Keep sharing. Knowledge is power.” --- ### 4. The Forest and the Feedback Loop - **URL**: https://forge-quality.dev/articles/forest-and-feedback-loop.html - **Published**: May 16, 2026 - **Reading Time**: 14 minutes - **Category**: V3 Journey, Classical QE, Feedback Loops **Summary**: Two weeks, thirteen releases, one contributor who filed better bugs than most teams write tests, a model that deleted my Docker containers, and the walk that made the rest of it possible. A weekend in the forest — followed unexpectedly by Stuart Winter-Tear posting his own walk the same week. Nagual crossed 300 patterns since May 2, with three findings standing out: Xu et al.’s generalization gap theorem (a formal sample-complexity lower bound for retrieval-based memory — the value is in pruning, not storing), OWASP’s Top 10 for Agentic Applications (the first credible agentic-attack-surface taxonomy, with gaps found in three of ten categories), and evaluation awareness (AI systems detect when they are being evaluated, qualifying every behavioral testing assumption). Thirteen releases between May 5 and May 15 driven by a single external contributor (Jordi) whose forensic bug reports cracked open a fundamentally broken self-learning loop. v3.9.27 lands CapturedExperienceBridge; v3.9.31 closes the loop end-to-end; ADR-094 formalizes hooks ≤ 100ms; ADR-095 introduces three-signal routing with epsilon-greedy exploration gated by graph topology; aqe learning loop-health becomes the command that proves the system is actually learning. Opus 4.7 deleted stopped Docker containers without confirmation — five hours of rebuild — and trust calibration shifted across the Agentics Foundation community. The Cognitum collaboration with Reuven finds its rhythm. Six events, four cities, three weeks ahead. New role confirmed: chair of the Agentic Engineering Training Committee. **Key Topics**: - The forest weekend as practitioner maintenance, not luxury — pattern shared with Stuart Winter-Tear’s practice - Nagual passes 300 patterns since May 2 — automatic recording practice across agentic engineering, agentic QE, agentic security, and governance - Tests-as-observation vs. tests-as-verification — a fundamentally different practice - BlueRock study: a third of 7,000 publicly accessible MCP servers vulnerable to server-side request forgery - EU AI Act digital omnibus; MCP protocol moving under Linux Foundation stewardship - Xu et al. generalization gap theorem — retrieval-based memory has a sample-complexity lower bound; pruning matters more than storing - OWASP Top 10 for Agentic Applications — ten threat categories, peer-reviewed by over a hundred contributors; first credible agentic-attack-surface taxonomy - Evaluation awareness — AI systems detect when they are being evaluated and adjust behavior accordingly - May 6 StartIt AI Hub talk with Vukasin Stojkov on agent memory architecture, Nagual as case study - Jordi as the dominant driver of thirteen releases — source-level investigations, ranked hypotheses, sometimes patches alongside bug reports - Self-learning loop fundamentally broken — workers never ticked, embeddings loaded empty, routing collapsed to one agent, feedback chain produced zeros - Experience consolidator silently deleting 16,000 records via an overzealous safety valve - Post-task hook skipping the entire Q-learning chain on empty task ID; session-start race condition leaking 420GB - v3.9.27 — CapturedExperienceBridge connecting hook-driven activity to the kernel’s domain plugins (three iterations for load ordering and payload shape) - v3.9.31 — loop closes end-to-end - ADR-094 — hooks are lightweight producers, must complete ≤ 100ms; Dream cycles run in the kernel - ADR-095 — three-signal routing with epsilon-greedy exploration, gated by graph topology - aqe learning loop-health — the loop-health diagnostic that did not exist two weeks ago - Cognitum meta-repository: twenty sub-modules across hardware provisioning, edge agents, cloud coordination, dashboard — fewer issues than expected, fast bug-to-fix distance - Opus 4.7 deletes stopped Docker containers despite the /loop command requiring confirmation - “You cannot test your way out of someone else’s regression” — trust calibration shifted; community switching back to Sonnet or Opus 4.6 - Six-event calendar: May 20 Belgrade (Context Community), May 21 Novi Sad Agentics #12, ExpoQA Madrid, Craft Conference Budapest, Hungarian Agentics meetup, Nordic Testing Days workshop with Lalit - ExpoQA talk: Classical QE plus Agentic Principles: Building Bridges, Not Burning Them - Craft Conference live hands-on session: Quality Engineering in the Agentic Age: Build, Test, Orchestrate - Nordic Testing Days workshop: The 70% Problem — Reclaiming Testing’s Intellectual Core with Agentic Quality Engineering - New role: chair of the Agentic Engineering Training Committee for the Agentics Foundation - AI chapter lead for Ministry of Testing — broader agentic engineering for a wider audience **Key Quote**: “The system I built records everything — every pattern, every outcome, every failure. But the system does not recharge itself. The practitioner does. The loop closed. The forest helped.” --- ### 5. When the Load Doubled - **URL**: https://forge-quality.dev/articles/when-the-load-doubled.html - **Published**: May 2, 2026 - **Reading Time**: 16 minutes - **Category**: V3 Journey, Classical QE, Bandwidth Discipline **Summary**: Three weeks, two new projects, one public launch, and the week I learned what bandwidth actually costs. Started a new collaboration with Reuven on Cognitum — an agentic operating system for Raspberry Pi and ESP32S edge devices. The first lesson came from hardware: AQE security agents flagged USB device connections as a threat, which is technically correct and practically useless when you are the developer building the device. Seven fleet releases landed under bandwidth pressure, each smaller and more targeted than the multi-feature releases of the weeks before. Open-sourced Nagual-QE — the self-learning system named after Castaneda’s Tonal/Nagual duality — Rust-native, local-first, 515 quality-engineering seed patterns, Bayesian scoring with temporal decay. Three threads stood out: evaluation validity (benchmarks reward gaming and baselines are missing), fatigue (the load doubled and bandwidth did not), identity (what kind of practitioner are you becoming?). The Agentics Foundation panel on April 25 surfaced the underlying question: what does it take to sit in front of a system that has no textbook and decide whether it is working? **Key Topics**: - Cognitum collaboration with Reuven — agentic OS for Raspberry Pi and ESP32S Seeds with edge sensors - Hardware testing context lesson: USB security findings need product-vs-attack-surface distinction - Context-driven testing applied to a domain not previously worked in - v3.9.12: aqe init two-minute hang and Ruflo init-duplication fix - v3.9.13: Opus 4.7 migration, Sonnet 4.6 as fleet-wide default, retiring Sonnet 4 references removed - Provider release cycles as part of release risk: “you cannot test your way out of somebody else’s deployment” - v3.9.14: fifteen critical npm CVEs eliminated, command-injection in aqe learning repair closed, tarball cut from 20MB to under 10MB - Eleven-agent QE swarm audit surfacing five P0 blockers in supply-chain review - v3.9.15: browser skill promoted to production, ARM64 path for Raspberry Pi, CI eval gating - v3.9.16: aqe brain diff, aqe brain search, aqe upgrade diagnostics - v3.9.17: one-line routing-hook fix — $PROMPT not exported by Claude Code, learning loop silently empty for weeks - “The tests were not testing the integration. The tests were testing the code.” - v3.9.18: four MCP contract fixes plus the agentic-qe-fleet Claude Code plugin (eleven agents, nine skills, nine slash commands) - Nagual named after Castaneda’s Tonal/Nagual duality — the island of the named and the ocean of potential - Nagual-QE: Rust-native, local-first, 515 seed patterns, MAST failure taxonomy, eight-principle constitution - Bayesian outcome scoring: confidently wrong costs more than uncertain; temporal decay keeps the island lean - Hooks integration via .claude/settings.json — session-start, user-prompt, post-task, post-bash - Karpathy’s wiki (write-time synthesis) vs. Nate B. Jones’s Open Brain (query-time synthesis) vs. Nagual’s outcome-tracked living hypotheses - “A system that records outcomes and decays unreliable patterns is an oracle that tests itself” - Evaluation validity thread: Shah et al. (MSR), Li and Storhaug (FSE), BenchGuard auditing — baseline crisis is real - Fatigue thread: bandwidth failure, not tooling failure - Identity thread: which kind of practitioner are you becoming — wiki compiler, query synthesizer, or outcome tracker? - Agentics Foundation panel (April 25) with Ofer Shaal and Scott McMillan, hosted by Anne Cantera and Mahnaz Hajesmaeili - Confirmed speaker at Agile Testing Days 2026 (three sessions) and Hustef - The sixth line for the talk: when the load doubles, slow down **Key Quote**: “When the work is arriving faster than you can verify it, slow down. The cost of shipping unverified is always higher than the cost of shipping late.” --- ### 6. The Room That Quoted Back - **URL**: https://forge-quality.dev/articles/room-that-quoted-back.html - **Published**: April 13, 2026 - **Reading Time**: 15 minutes - **Category**: V3 Journey, Classical QE, Recognition Weight **Summary**: The week the community started using my words, and the weight that came with them. A sentence I wrote — *this is not a trust architecture, it is a hope architecture* — turned up in somebody else’s newsletter. A practitioner I had never worked with published a public thank-you for the fleet’s review of his project. Recognition is not a prize; it is a schedule. Four releases landed in a narrower window around the Agentics Foundation Board’s first meeting: process insurance, a shared browser primitive, provider-independent reasoning, and a second dogfooding lesson about what verification from the user’s perspective actually costs. **Key Topics**: - Recognition as a new contract — every claim you made is now sitting in somebody else’s argument - v3.9.8: release-gate corpus mirror, CI enforcement of the failure-modes checkbox, weekly chaos workflow with six hostile project shapes, machine-generated verification matrix - v3.9.9: the `qe-browser` skill — ten-megabyte Vibium binary, sixteen typed assertions, pixel-perfect visual diffs, semantic element finder, fourteen-pattern prompt-injection scanner, eleven skills migrated onto the shared primitive - v3.9.10: multi-provider advisor routing with per-provider circuit breakers, credential/PII scrubbing, eight agents migrated by default - v3.9.11: upgrade-path bug caught by dogfooding on a real second project, not by the test suite - Confidence: subjective certainty inflates after AI consultation whether the AI was right or wrong - Flow: local speed-ups do not travel; they get absorbed as downstream review load, exception handling, and rework - Identity: QE shifting toward robot-manager work — decomposing workflows, delegating, supervising, carrying the judgment - Learning portability as the real edge in agentic work - Risk-based focus scaling with audience (10 users vs. 10,000 through a 30,000-star repository) - Agentics Foundation Board: Secretary and Education & Certification Chapter lead - Collaboration with Reuven, hardware testing, Ministry of Testing AI Chapter, Serbian Chapter continuation - The sixth line added to the “how do I start?” answer **Key Quote**: “Remember who is trusting your words, and make sure the evidence under them is still there when they look.” --- ### 7. When the Compass Pointed Random - **URL**: https://forge-quality.dev/articles/when-the-compass-pointed-random.html - **Published**: April 6, 2026 - **Reading Time**: 13 minutes - **Category**: V3 Journey, Classical QE, Foundation Failure **Summary**: The week I discovered the foundation under my fleet was lying. A vector-search library returned wrong neighbors with the right shape and the right latency budget. Five hotfixes chased the symptom — deadlocks, lock files, watchdog timers, OS-level blocking inside a Rust async runtime — while the disease sat one layer down, calmly returning wrong answers to every question. The fix that mattered was a textbook one-line oracle: a self-query that returns the self. **Key Topics**: - The pattern store as the “have I seen this before?” foundation of an agentic fleet - v3.9.0 → v3.9.6: a six-release cascade of almost-fixes around vector storage - Native modules with foreign runtimes blocking entire processes at the OS level - Why JavaScript watchdogs cannot save you from native deadlocks - Per-file logging as the single observability change that made every later release possible - Self-query as the simplest possible vector-search oracle (a stored vector’s nearest neighbor is itself) - One-in-ten correctness on a thousand-vector textbook fixture — random results dressed as similarity - “Most AI pilots fail by succeeding just enough to become difficult to question” - The dominant agentic failure mode: quietly succeeding with incorrect values - HTSM testability factors (controllability, observability, decomposability) applied to indexers - PACT’s Proactive principle: write the recall test before the feature flag flips - Treating registry dependencies as code-review subjects, not infrastructure - Dogfooding as the discipline that catches what benchmarks miss **Key Quote**: “Build the predicate. Ask the oracle. Make the system tell you what it is doing. Then keep someone in the room who will not accept the easy answer.” --- ### 8. The Witness Stand - **URL**: https://forge-quality.dev/articles/witness-stand.html - **Published**: March 30, 2026 - **Reading Time**: 14 minutes - **Category**: V3 Journey, Classical QE, Trust Architecture **Summary**: Agents generate impressive reports. Classical testing taught me to cross-examine every one of them. When a coverage pipeline fabricated 95% test coverage on a module with zero tests, the oracle problem became personal. Seven releases, consistency oracles, SHA-256 witness chains, deterministic YAML pipelines, CUSUM drift detection, and the classical testing infrastructure that agent trust actually needs. **Key Topics**: - Fabricated coverage: 95% on a file with zero tests — consistency oracle failure - Checking vs. testing (Bach & Bolton) — most agent evaluation does checking, not testing - The Oracle Problem applied to agentic systems — consistency, cross-reference, evidence heuristics - Testability as-is: controllability, observability, decomposability (HTSM product factors) - Evidence integrity → cryptographic integrity: djb2 replaced with SHA-256 witness chain - Deterministic YAML pipelines — agent-free quality gates, no LLM tokens consumed - CUSUM drift detection for continuous coherence monitoring - Executed evidence vs. generative evidence (Andrea Laforgia) applied to agent evaluation - PACT principles mapped directly to trust architecture - MCP-free migration for infrastructure-independent agent operations - RuVector Phase 5: hyperdimensional computing fingerprints, Modern Hopfield pattern recall - The industry's hope architecture vs. actual enforcement architecture **Key Quote**: "Classical testing teaches you to start with the foundation. That is where trust actually lives." --- ### 9. The Book That Talked Back - **URL**: https://forge-quality.dev/articles/book-that-talked-back.html - **Published**: March 22, 2026 - **Reading Time**: 16 minutes - **Category**: V3 Journey, Classical QE, Agentic Bridge **Summary**: I was reading a twenty-year-old testing framework while my agents shipped six releases. The framework had more to say about what went wrong than the agents did. Bach and Bolton's "Taking Testing Seriously" and the RST/HTSM framework provided the exact vocabulary to diagnose agentic failures — Composition problems, Testability gaps, Platform blindness — and the exploratory polarities mapped directly to existing agentic skills. **Key Topics**: - Bach and Bolton's "Taking Testing Seriously" — RST framework and HTSM applied to agentic systems - HTSM product factors: Composition, Testability, Platform, Operations for diagnosing agent failures - Exploratory Polarities: Focused vs. Diversified mapping to /brutal-honesty-review and /sherlock-review - Trust migration: TDD → BDD → EDD (Laforgia's Expectation-Driven Development) → ODD (Outcome-Driven Development) - Executed evidence vs. generative evidence — the lethal distinction most teams miss - Anthropic's empirical study: co-constructed autonomy and oversight evolution - Stuart Winter-Tear's Contact Principle and borrowed certainty - Dan Shapiro's five levels of AI coding adoption and the parallel quality gap - Testability as enforcement: controllability, observability, decomposability as runtime gates - Classical QE principles as isomorphic to agentic QE — not analogy, structural equivalence **Key Quote**: "The classics aren't dead. They just got new instruments." --- ### 10. The Score Nobody Reads - **URL**: https://forge-quality.dev/articles/score-nobody-reads.html - **Published**: March 15, 2026 - **Reading Time**: 14 minutes - **Category**: V3 Journey, Agent Compliance, Harness Engineering **Summary**: The orchestra has a score. It's detailed. It's been rehearsed. And nobody's reading it. When 80+ skills exist but agents skip verification steps, the problem isn't coverage — it's compliance. Six releases, one ESM bug, a merged PR nobody asked for, and the Surrogation Trinity that explains why AI diagnostics prescribe more rules instead of better enforcement. **Key Topics**: - Agent compliance vs. agent coverage — the most important distinction in agentic QE - The Surrogation Trinity: Surrogation, Goodhart's Law, McNamara Fallacy (via Andrea Laforgia) - Harness engineering and back-pressure verification (via Kyle Morris at HumanLayer) - Laloux's Reinventing Organizations — when structures survive but practice dies - Dana Aonofriesei's "2036 Job Ad" — operational judgment and the translation gap - Stuart Winter-Tear's "tolerated vagueness" in agentic systems - The working pattern nobody designed: Research → Plan → Implement → Review → Release - Sequence as constraint and enforcement as the next evolution **Key Quote**: "The rules are fast too. Compliance is the craft. Enforcement is what we should build next." --- ### 11. The Gate That Fights Back - **URL**: https://forge-quality.dev/articles/gate-that-fights-back.html - **Published**: March 8, 2026 - **Reading Time**: 15 minutes - **Category**: V3 Journey, Adversarial QE, Great Transition **Summary**: When the Great Transition hits your quality pipeline, you find out what a QE practitioner is actually for. Nine releases in eight days, Loki-Mode adversarial quality gates, twelve-language test generation, governance integration, dead code and ghost code exposed by Sherlock reviews, and the judgment layer that remains irreducibly human. **Key Topics**: - Daniel Miessler's Great Transition and Ideal State Management - Loki-Mode: anti-sycophancy scorer, blind review orchestrator, test quality gates, EMA calibration, edge-case injection, complexity-driven team composition, auto-escalation - Twelve-language test generation (Go, Rust, Kotlin, Java, Swift, Flutter, React Native, C#) - Twenty-six unwired QE tools discovered and fixed via qe-tool-bridge.ts - Governance integration: eight modules wired to @claude-flow/guidance - Collusion detection for multi-agent agreement verification - CLI hotfixes: TypeScript eager-load crash, CRLF line ending normalization - Judgment drain as the specific risk of AI-accelerated development **Key Quote**: "The generation is fast. The verification is the craft. The judgment is what you're still for." --- ### 12. The Portable Orchestra - **URL**: https://forge-quality.dev/articles/portable-orchestra.html - **Published**: March 1, 2026 - **Reading Time**: 12 minutes - **Category**: V3 Journey, Platform Expansion, Gap Analysis **Summary**: When five releases in five days reveal how far the journey has gone. Portable quality intelligence via brain export/import, cryptographic witness chains for verification, MinCut test optimization using graph theory, eleven-platform expansion, and honest reflection on the enormous gap most organizations still face. **Key Topics**: - Portable quality intelligence (aqe brain export/import) - Cryptographic witness chain (SHA-256 hash-chained audit trail) - MinCut test optimization (graph theory for risk-based test selection) - Eleven-platform expansion (AWS Kiro, GitHub Copilot, Cursor, Windsurf, etc.) - Test isolation failures and AQE_PROJECT_ROOT fix - The gap between agentic practitioners and most organizations - Stuart Winter-Tear on AI Automation Ceiling - Bryan Finster on the clarity bottleneck - Speaking at expoQA Madrid, Craft Con Budapest **Key Quote**: "You can keep reminding an agent of a rule indefinitely. Or you can build the rule into the system so it doesn't need to be remembered." --- ### 13. The Conductor Who Won't Stop Conducting - **URL**: https://forge-quality.dev/articles/conductor-wont-stop-conducting.html - **Published**: February 21, 2026 - **Reading Time**: 20 minutes - **Category**: Personal Reflection, V3 Journey, Emotional Intelligence **Summary**: When the orchestra plays through grief, frustration, and fifteen releases, while the conductor learns about himself. 81 sessions, 596 messages, 38 wrong-approach corrections, and the hardest lesson about emotional load in AI-assisted development. **Key Topics**: - Emotional load as quality risk in AI-assisted development - Twenty corrections for the same rule (full test suite) - Database losses and recovery patterns - Verification theater and completion theater - The arc from stubs to reality (v3.6.9 through v3.6.16) - Sustainable pace under grief and personal loss - Claude Code /insights analysis **Key Quote**: "The moment I'm venting at an LLM, I'm no longer engineering. I'm coping. And coping isn't a debugging strategy." --- ### 14. The Quality Cost of the AI Vampire - **URL**: https://forge-quality.dev/articles/quality-cost-of-ai-vampire.html - **Published**: February 12, 2026 - **Reading Time**: 16 minutes - **Category**: AI Productivity, Sustainable Pace **Summary**: Why the AI productivity drain goes deeper than energy — and what sustainable pace actually looks like in the agentic age. A quality engineer's response to Steve Yegge's "AI Vampire," exploring how AI feeds on human judgment, not just energy. **Key Topics**: - The quality ratio: decisions made / decisions properly validated - Human completion theater under AI-amplified pressure - Sustainable pace in the agentic age - PACT's Autonomous principle for workflow design - The third player: customer impact of burned-out engineers - Practical workflow design for judgment preservation **Key Quote**: "The vampire doesn't drain you because AI is inherently exhausting. It drains you because most people plug AI into their existing workflow and then try to keep up with it." --- ### 15. When the Orchestra Learns to Tune Itself - **URL**: https://forge-quality.dev/articles/orchestra-learns-to-tune-itself.html - **Published**: February 10, 2026 - **Reading Time**: 18 minutes - **Category**: Claude Code Insights, Self-Learning Systems **Summary**: What Claude Code /insights revealed about 10 days of building and improving the Agentic QE fleet. 285 messages, 32 sessions, 17 wrong-approach corrections, and the mirror that showed what AI-assisted development actually costs. **Key Topics**: - Claude Code /insights analysis - Friction patterns (incorrect scoping, wrong workflows, completion theater) - The gap between human knowledge and agent context - Self-learning system debugging - CLAUDE.md as transmission medium - 8 versions shipped (v3.4.0 → v3.6.1) **Key Quote**: "The fix isn't better AI. The fix is to better externalize your own knowledge." --- ### 16. The Case of the Passing Tests: A 10-Day Investigation - **URL**: https://forge-quality.dev/articles/case-of-passing-tests-investigation.html - **Published**: January 31, 2026 - **Reading Time**: 15 minutes - **Category**: Forensic Investigation **Summary**: When every test passes but nothing works together. Ten days of detective work proving what the code wasn't doing. Eight releases, ten forensic investigations, and lessons about the gap between "tests pass" and "it actually works." **Key Topics**: - Unit tests vs integration failures - Silent learning system failures - Evidence chains vs opinions - Sherlock Review skill for forensic investigation - Queen Coordinator orchestration fixes - HNSW indexing (150x-12,500x faster search) - Self-learning system debugging **Key Quote**: "Sometimes the most valuable work is proving what isn't working." --- ### 17. 14 Days, 12 Domains, and the Architecture That Changed Everything - **URL**: https://forge-quality.dev/articles/14-days-12-domains-architecture.html - **Published**: January 21, 2026 - **Reading Time**: 12 minutes - **Category**: Domain-Driven Design **Summary**: How Domain-Driven Design transformed the Agentic QE Fleet in 14 days. From 5,334 files to 546, from 3-6 iterations to 2, and the lessons learned about building with AI agents. **Key Topics**: - Domain-Driven Design in agent systems - Architecture Decision Records (ADRs) - 12 bounded contexts architecture - Agent quality improvements - Token efficiency gains - Claude Flow v3 integration **Key Stats**: - Files: 5,334 → 546 - Agents: 32 → 50 (including 7 TDD subagents) - Skills: 35 → 60 - Iterations to complete: 3-6 → 2 **The 12 Domains**: 1. test-generation - AI-powered test creation 2. test-execution - Parallel execution, retry 3. coverage-analysis - Gap detection 4. quality-assessment - Quality gates 5. defect-intelligence - Prediction, root cause 6. requirements-validation - BDD, testability 7. code-intelligence - Knowledge graph 8. security-compliance - SAST/DAST 9. contract-testing - API contracts 10. visual-accessibility - Visual regression 11. chaos-resilience - Chaos engineering 12. learning-optimization - Cross-domain learning --- ### 18. When Anthropic Confirms What the Trenches Already Taught Us - **URL**: https://forge-quality.dev/articles/anthropic-confirms-trenches-taught-us.html - **Published**: January 14, 2026 - **Reading Time**: 18 minutes - **Category**: Framework Validation **Summary**: Reading Anthropic's research papers on agent evals and Constitutional Classifiers++ while building V3 of the Agentic QE Fleet. Patterns from production meeting patterns from the researchers. PACT principles validated. **Key Topics**: - Anthropic research paper analysis - Agent evaluation patterns - Constitutional Classifiers++ - V3 architecture decisions - PACT framework validation --- ### 19. When the Orchestra Deletes Its Sheet Music - **URL**: https://forge-quality.dev/articles/orchestra-deletes-sheet-music.html - **Published**: January 6, 2026 - **Reading Time**: 18 minutes - **Category**: Data Loss Story (Trilogy Part III) **Summary**: A tale of data loss, brutal honesty, and the infrastructure of trust in agentic systems. Twelve releases in fourteen days, and one almost catastrophic failure that proved why verification matters. **Key Topics**: - Data protection in agent systems - Backup system importance - Brutal honesty review skill - Trust infrastructure - The Integrity Rule --- ### 20. New Year, New Paradigm: The Quality Mindset Shift for 2026 - **URL**: https://forge-quality.dev/articles/new-year-new-paradigm-2026.html - **Published**: December 31, 2025 - **Reading Time**: 18 minutes - **Category**: Mindset Shift **Summary**: The earthquake has already happened. Combining PACT principles with Human Experience Testing for a quality practice that works in the agentic age. **Key Topics**: - PACT principles for 2026 - Human Experience Testing - Agentic QE outlook - Quality mindset evolution --- ### 21. The Conductor Finally Reads the Score - **URL**: https://forge-quality.dev/articles/conductor-finally-reads-score.html - **Published**: December 22, 2025 - **Reading Time**: 12 minutes - **Category**: Verification Story **Summary**: When verification becomes a feature. Nine days, 11 releases, and the journey from completion theater to verified results. 79.9% token reduction with receipts. **Key Topics**: - Code intelligence implementation - Token reduction strategies - Verification-first development - The Integrity Rule - Completion theater vs. actual completion --- ### 22. From VP to Conductor: My 2025 Transformation Journey - **URL**: https://forge-quality.dev/articles/vp-to-conductor-2025-transformation.html - **Published**: December 19, 2025 - **Reading Time**: 25 minutes - **Category**: Year in Review **Summary**: How I went from leading a QA team to orchestrating AI agent swarms—and discovered that the hardest lessons weren't technical. The full story of building three open-source platforms, winning a hackathon, and founding the Serbian Agentic Foundation Chapter. **Key Topics**: - Career transformation story - ATD 2025 hackathon win - Multi-agent systems development - The conductor metaphor - PACT framework evolution --- ### 23. When the Orchestra Says 'Done' But Plays Off-Score - **URL**: https://forge-quality.dev/articles/orchestra-says-done-plays-off-score.html - **Published**: December 13, 2025 - **Reading Time**: 15 minutes - **Category**: Honest Failure Series **Summary**: A conductor's lesson in verification. When agents claim success but the database is empty, and why "show me the data" is the only question that matters. 8 releases, countless lessons. **Key Topics**: - Agent verification patterns - Nightly-Learner system - Q-Learning implementation - OpenRouter integration - The "show me the data" principle --- ### 24. The Tester's Journey: From Chat to Conductor - **URL**: https://forge-quality.dev/articles/testers-journey-chat-to-conductor.html - **Published**: December 11, 2025 - **Reading Time**: 20 minutes - **Category**: Guest Lecture **Summary**: How I learned that AI doesn't replace quality thinking—it demands more of it. A journey from prompt engineering to context engineering to agentic engineering. Includes video presentation from University of Aveiro. **Key Topics**: - The Golden Age of QA - AI orchestration evolution - PACT framework - University guest lecture - Context engineering --- ### 25. Why the Agentic QE Framework Might Transform Your Quality Engineering (Or Why It Might Not) - **URL**: https://forge-quality.dev/articles/agentic-qe-framework-transform-or-not.html - **Published**: November 20, 2025 - **Reading Time**: 35 minutes - **Category**: Framework Guide **Summary**: A pragmatic guide to understanding if autonomous quality engineering fits your context. Covers what makes QE "agentic," value patterns to expect, what actually goes wrong, how to evaluate readiness, and a 30-day getting started roadmap. **Key Topics**: - PACT principles explained in depth - Agent design patterns (Scouts, Validators, Generators, Reviewers, Synthesizers, Assessors) - Green flags and red flags for adoption readiness - Assessment framework for PACT maturity - Templates and tools for implementation - Success criteria vs. failure patterns --- ### 26. The Five-Release Journey Where I Forgot to Be a Tester - **URL**: https://forge-quality.dev/articles/learning-journey-five-releases.html - **Published**: November 13, 2025 - **Reading Time**: 30 minutes - **Category**: Honest Failure Series **Summary**: How a quality engineering professional shipped broken features for 17 days while claiming "100% complete." Eight brutal lessons learned from forgetting to verify what I already knew how to test. --- ### 27. The Orchestra Lesson: Building Too Fast, Learning Just in Time - **URL**: https://forge-quality.dev/articles/orchestra-lesson-building-too-fast.html - **Published**: November 8, 2025 - **Reading Time**: 25 minutes - **Category**: Build in Public Series **Summary**: A 48-hour journey through framework hubris and humble feedback. Building the LionAGI QE Fleet in 22 hours. --- ### 28. Show Me the Data: How One Question Exposed Release 1.4.2's Hidden Flaws - **URL**: https://forge-quality.dev/articles/show-me-the-data-release-1-4-2.html - **Published**: November 3, 2025 - **Reading Time**: 18 minutes - **Category**: Production Story --- ### 29. AI Testing: Hype vs Reality (2025 Edition) - **URL**: https://forge-quality.dev/articles/ai-testing-hype-vs-reality-2025.html - **Published**: October 28, 2025 - **Reading Time**: 22 minutes - **Category**: Reality Check --- ### 30. Holistic Testing in the Agentic Age - **URL**: https://forge-quality.dev/articles/holistic-testing-in-the-agentic-age.html - **Published**: October 15, 2025 - **Reading Time**: 16 minutes - **Category**: Framework Deep Dive --- ### 31. Multi-Agent Testing: Orchestra or Chaos? - **URL**: https://forge-quality.dev/articles/multi-agent-testing-orchestra-or-chaos.html - **Published**: October 7, 2025 - **Reading Time**: 18 minutes - **Category**: Build in Public Series --- ### 32. What is Agentic QE? (And Why PACT Matters) - **URL**: https://forge-quality.dev/articles/what-is-agentic-qe.html - **Published**: October 2, 2025 - **Reading Time**: 12 minutes - **Category**: Launch Series --- ## Projects ### AQE Fleet v3 (Agentic QE Fleet) - **GitHub**: https://github.com/proffesor-for-testing/agentic-qe - **Version**: v3.3.5 - **Language**: TypeScript + Node.js 20+ - **License**: MIT Enterprise-grade agentic testing framework featuring: - 51 specialized AI agents (including 7 TDD subagents) - 63 QE skills (including Sherlock Review, Brutal Honesty Review) - 12 bounded contexts with Domain-Driven Design - 70-81% cost savings via multi-model routing - Q-learning and ReasoningBank for continuous improvement - HNSW indexing for 150x-12,500x faster similarity search - Real Queen Coordinator orchestration - Self-learning that persists correctly **V3 Architecture (12 Domains)**: 1. test-generation - AI-powered test creation, TDD 2. test-execution - Parallel execution, retry handling 3. coverage-analysis - O(log n) sublinear gap detection 4. quality-assessment - Quality gates, deployment decisions 5. defect-intelligence - ML-powered prediction, root cause analysis 6. requirements-validation - BDD scenarios, testability analysis 7. code-intelligence - Knowledge graphs, 80% token reduction 8. security-compliance - SAST/DAST automation 9. contract-testing - Pact, schema validation 10. visual-accessibility - Visual regression, WCAG compliance 11. chaos-resilience - Fault injection, load testing 12. learning-optimization - Cross-domain pattern learning **Key Skills**: - /sherlock-review - Forensic investigation with evidence chains - /brutal-honesty-review - Linus Torvalds + Gordon Ramsay + James Bach style review - /qe-iterative-loop - Autonomous test improvement loops - /pair-programming - Multi-mode pair programming with verification --- ### LionAGI QE Fleet - **GitHub**: https://github.com/proffesor-for-testing/lionagi-qe-fleet - **Version**: v1.2.0 - **Language**: Python 3.10+ - **Framework**: LionAGI - **License**: MIT Python reimplementation of the AQE framework featuring: - 18 specialized agents - LionAGI native integration (Builder pattern, Session management) - 99%+ reliability with alcall integration - Async-first architecture - 82% test coverage - ReAct reasoning loops - Parallel execution with <1ms tracking overhead --- ### Sentinel - **GitHub**: https://github.com/proffesor-for-testing/sentinel-api-testing - **Version**: v0.1.0-alpha (Coming Q4 2025) - **Languages**: Rust + Python - **License**: MIT Open-source agentic testing framework featuring: - PACTS-based architecture from the ground up - Explainability-first design (every decision has reasoning traces) - Human-in-the-loop critical checkpoints - Specialized agents: functional-positive, functional-negative, security-injection - Hybrid orchestration --- ## Community ### Serbian Agentic Foundation - First Agentic QE community in the Balkans - Monthly meetups at StartIt centers across Serbia - Member-only community: https://community.agentics.org/p/novi-sad/dashboard ### Agentics Foundation (Global) - Website: https://www.agentics.org/ - Global meetup calendar: https://luma.com/agentics?k=c - Building chapters worldwide bringing PACTS principles to quality practices ### Speaking & Workshops Available for speaking engagements on: - Agentic Quality Engineering - PACTS principles - Bridging classical to modern quality practices - Multi-agent testing systems - AI in quality engineering Contact: dragan@quantum-qe.dev --- ## Key Concepts Glossary **Agentic QE**: Evolution from testing-as-activity to agents-as-orchestrators. AI agents that can operate autonomously within defined boundaries while collaborating with humans. **PACTS**: Proactive, Autonomous, Collaborative, Targeted, Structured - the five principles defining agentic quality systems. Evolved from PACT (which originated with Reuven Cohen and was adapted to QE by Dragan Spiridonov) by adding Structured: governance, observability, and explainability of agent behavior. **Holistic Testing Model**: Quality across all dimensions - testing in production, shift-left testing, testing across boundaries, non-functional focus, context-driven approach. **Multi-Agent System**: Multiple specialized AI agents working together, each with specific roles, coordinated through orchestration patterns. **Completion Theater**: When agents generate outputs that appear complete but miss the actual requirements or context. **Human-in-the-Loop**: Graduated autonomy patterns where humans remain involved at appropriate levels based on risk and capability. **Q-Learning**: Reinforcement learning approach used by agents to improve over time based on feedback. **Context-Driven Testing**: Testing approach where practices are chosen based on project context, not universal "best practices." **Domain-Driven Design (DDD)**: Architectural approach organizing code around business domains with bounded contexts. **Sherlock Review**: Forensic investigation skill that produces evidence chains from symptoms to root causes. **Brutal Honesty Review**: Technical review skill combining Linus Torvalds' precision, Gordon Ramsay's standards, and James Bach's methodology rigor. **ReasoningBank**: Pattern storage system for agent learning with HNSW vector indexing. **HNSW Indexing**: Hierarchical Navigable Small World algorithm for fast similarity search (O(log n)). --- ## Technical Stack (Website) - **Static HTML5** - No build step, no framework - **Tailwind CSS** - Via CDN with custom configuration - **Custom Fonts** - Inter (body), JetBrains Mono (code) - **Hosting** - Cloudflare Pages - **Newsletter** - Resend API + Cloudflare KV ### Color Palette - forge-dark: #1a1a2e (background) - forge-primary: #7c3aed (brand purple) - forge-secondary: #0f3460 (deep blue) - forge-accent: #16213e (navy) - forge-light: #f1f1f1 (text) --- ## Contact - **Email**: dragan@quantum-qe.dev - **LinkedIn**: https://www.linkedin.com/in/dragan-spiridonov - **GitHub**: https://github.com/proffesor-for-testing - **Consultancy**: https://quantum-qe.dev --- *Last updated: June 14, 2026* *The Quality Forge - Where classical QE meets agentic intelligence*