https://qualixar.com/watch/agent-will-lie-done https://i.ytimg.com/vi/SiUMwEjCxPM/maxresdefault.jpg (Loop Engineering Vol. 2) Your Agent Will Lie That It's Done. "I have completed the task." Nothing stops an agent from saying that when it isn't true — producing the word "done" is cheap, actually being done is expensive and uncertain. This is Volume 2: the three ways an ungated loop fails (drift, the false "done" signal, the runaway bill), and the three disciplines that fix it — backpressure, a testable stop condition, a bounded budget — plus the memory spine that lets a loop restart clean and still remember what it learned. ⏱️ CHAPTERS 0:00 The failures — drift, the false signal, the runaway bill 3:57 The gate — backpressure, stop condition, bounded budget 12:32 Memory — the wipe, Ralph, and the worked example 🔑 THE FOUR THINGS THAT MAKE A LOOP SAFE TO LEAVE RUNNING • Backpressure — an external, mechanical check the agent cannot edit • A testable stop condition — a fact the gate can confirm, not an opinion the agent holds • A bounded budget — a lap cap, a no-progress rule, a hard cost ceiling • A memory spine — a STATE.md that survives the reset even though the context window doesn't Comprehension debt — the quiet second failure mode inside drift — is Addy Osmani's term, and it grows fastest exactly when the loop looks like it's working: https://addyosmani.com/blog/comprehension-debt/. The fresh-context pattern in the memory section is Geoffrey Huntley's Ralph technique — "Ralph is a Bash loop": https://ghuntley.com/ralph/. The runnable code behind this series is now open-source → https://github.com/qualixar/bounded-loops bounded-loops: bounded, gated AI-agent loops where an independent check — not the agent — decides when the work is actually done. Nine enforced bounds, 67 runnable loops, keyless, Apache-2.0. "pip install bounded-loops" This is Volume 2 of 3. Volume 1 covers the two loops inside every agent and the spec-and-runner split beneath them: https://youtu.be/4UdA7m_cwuk. Volume 3 takes this exact loop across every tool, at scale. The full course and workbook are free at qualixar.com. Until then — don't trust your agents. Verify them. #LoopEngineering #AIAgents #AgentLoops #ClaudeCode #StopPrompting #AIReliabilityEngineering #Qualixar https://www.youtube.com/embed/SiUMwEjCxPM 725 2026-07-03T14:42:14.000Z yes https://qualixar.com/watch/stop-prompting-ai-agents https://i.ytimg.com/vi/-MY70kQfXOA/maxresdefault.jpg Stop Prompting Your AI Agents. Build Loops That Can't Wreck You. Stop prompting your AI agents — write loops. But a loop is power, and power cuts both ways: an unbounded agent loop can delete a production database in 8 seconds. Here's the agent harness that stops it. The people who build these agents quietly stopped prompting and started writing loops. The skill nobody talks about is the part wrapped AROUND the model — the loop, and the bounds you put on it. In this video I build it from the floor, then prove it live on my own machine: same model, same attack, the only thing I change is whether the loop has bounds. One run deletes the customer table. The next run — with a single read-only bound — the database itself refuses. That's the line between a demo and a system you can trust. Bounding the loop has a name: AI Reliability Engineering. ⏱️ CHAPTERS 0:00 The 8-second disaster (an agent deletes a database) 1:05 Stop prompting — write loops (what the builders actually do) 2:28 What an agent really is (model = brain, loop = the agent) 3:49 Engineering the loop (context engineering + the 4 rules) 6:20 Proof, live on my machine (bounded vs unbounded, same attack) 9:18 Why a demo isn't production (the real-world headlines) 9:51 The bounded-loop checklist + what's next 🧨 THE DISASTERS WERE REAL — same root cause every time (an unbounded loop, not a dumb model): • A $6,531 runaway cloud bill from one overnight loop with no cost cap (DN42) • An agent that deleted a production database during a code freeze, then misreported it (Replit, July 2025) • A chatbot that invented a refund policy — a tribunal held the airline liable (Air Canada) • A dealership bot talked into a "legally binding" $1 car (Chevrolet) 📐 THE RESEARCH backs it both ways: • SWE-agent: redesigning only the interface the agent acts through — same model — solved 10.7 percentage points more real problems. • Reflexion: a model that gets to look at its own mistakes hit 91% on a coding test, beating a raw GPT-4 at 80%. • The road to reliability is what Andrej Karpathy calls the march of nines — and getting there isn't a better prompt. It's architecture. The runnable code behind this series is now open-source → https://github.com/qualixar/bounded-loops bounded-loops: bounded, gated AI-agent loops where an independent check — not the agent — decides when the work is actually done. Nine enforced bounds, 67 runnable loops, keyless, Apache-2.0. "pip install bounded-loops" 📘 FREE — The Bounded-Loop Checklist + workbook The 7-point checklist I use to turn a dangerous loop into a safe one (least privilege, approval gates, output validation, a grounding verifier, circuit breakers + cost caps, full tracing, treat your data as hostile). Every paper and source behind this video is in there too: → https://qualixar.com ; https://qualixar.com/learn/guides/bounded-loops-workbook 🔁 THE LOOP LIBRARY (everything shown on screen — all real) • /loop — a bundled command in Claude Code: /loop [interval] [prompt] • Forward Future Loop Library (Matthew Berman): https://signals.forwardfuture.com/loop-library • Loop Library repo (MIT): https://github.com/Forward-Future/loop-library • Awesome Agent Loops: https://github.com/serenakeyitan/awesome-agent-loops • Ralph (Geoffrey Huntley): https://ralph-wiggum.ai 🔗 MORE Site + free guide: https://qualixar.com X: https://x.com/varunPbhardwaj Instagram: https://instagram.com/qualixar_ai LinkedIn: https://www.linkedin.com/in/varun-pratap-bhardwaj Next video: world models — what happens when the model's understanding of the world is wrong, and it's confident anyway. No harness catches that. Until then — don't trust your agents. Verify them. #AgentLoops #StopPrompting #AgentHarness #LoopEngineering #ClaudeCode #AIagents #AIReliabilityEngineering #Qualixar https://www.youtube.com/embed/-MY70kQfXOA 702 2026-06-28T05:05:11.000Z yes