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  <title>ai-learning-bits</title>
  <link>https://ai.jakubjirak.com/</link>
  <description>A professional blog on AI coding tools — Claude Code, GitHub Copilot, Codex, Gemini — agent architecture, local models, cost/token savings, and a sortable LLM benchmark.</description>
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  <item>
    <title>Claude Code, Copilot, Codex, Gemini: picking your pair-programmer in 2026</title>
    <link>https://ai.jakubjirak.com/p/ai-coding-tools-2026</link>
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    <pubDate>Sun, 21 Jun 2026 12:00:00 +0000</pubDate>
    <category>landscape</category>
    <description>Four agents now sit between you and your editor. They are not interchangeable. A field guide to what each is actually good at — and where the seams show.</description>
  </item>
  <item>
    <title>Claude Code: agentic coding from the terminal</title>
    <link>https://ai.jakubjirak.com/p/claude-code</link>
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    <pubDate>Sat, 20 Jun 2026 12:00:00 +0000</pubDate>
    <category>agents</category>
    <description>A planning loop, multi-file edits, and your test suite as the oracle. What the terminal-native agent gets right, and how to drive it.</description>
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  <item>
    <title>GitHub Copilot in 2026: from autocomplete to background agent</title>
    <link>https://ai.jakubjirak.com/p/github-copilot</link>
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    <pubDate>Fri, 19 Jun 2026 12:00:00 +0000</pubDate>
    <category>copilot</category>
    <description>Ghost-text was the gateway drug. The interesting Copilot now is the one that opens pull requests while you&#x27;re at lunch.</description>
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  <item>
    <title>Codex and GPT-5: OpenAI&#x27;s autonomous coding stack</title>
    <link>https://ai.jakubjirak.com/p/codex-gpt5</link>
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    <pubDate>Thu, 18 Jun 2026 12:00:00 +0000</pubDate>
    <category>openai</category>
    <description>A CLI and a cloud agent tuned for long, unattended runs in a sandbox. What &#x27;let it grind&#x27; actually buys you.</description>
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  <item>
    <title>Gemini for developers: a million tokens of context in practice</title>
    <link>https://ai.jakubjirak.com/p/gemini</link>
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    <pubDate>Wed, 17 Jun 2026 12:00:00 +0000</pubDate>
    <category>google</category>
    <description>The 1M-token window isn&#x27;t a bigger version of the same tool. It changes what &#x27;give it the codebase&#x27; means — and what breaks when you do.</description>
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  <item>
    <title>AI agent architectures that don&#x27;t fall over</title>
    <link>https://ai.jakubjirak.com/p/agent-architecture</link>
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    <pubDate>Tue, 16 Jun 2026 12:00:00 +0000</pubDate>
    <category>architecture</category>
    <description>Context, tools, memory, and evals — the boring scaffolding that decides whether your agent is a product or a demo.</description>
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  <item>
    <title>Running capable code models locally: Ollama, llama.cpp, vLLM</title>
    <link>https://ai.jakubjirak.com/p/local-models</link>
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    <pubDate>Mon, 15 Jun 2026 12:00:00 +0000</pubDate>
    <category>local</category>
    <description>When the code can&#x27;t leave the building, or you just want zero marginal cost. What&#x27;s realistic on a laptop, a workstation, and a server in 2026.</description>
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  <item>
    <title>What hardware actually runs these models — decently</title>
    <link>https://ai.jakubjirak.com/p/hardware-for-local-llms</link>
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    <pubDate>Sun, 14 Jun 2026 12:00:00 +0000</pubDate>
    <category>hardware</category>
    <description>VRAM is the gate, quantization is the key, and Apple&#x27;s unified memory quietly changed the math. A buyer&#x27;s guide by model size, not by hype.</description>
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  <item>
    <title>GLM-5.2 shipped without benchmarks — and that&#x27;s the story</title>
    <link>https://ai.jakubjirak.com/p/glm-5-2-no-benchmarks</link>
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    <pubDate>Sun, 14 Jun 2026 12:00:00 +0000</pubDate>
    <category>analysis</category>
    <description>Z.ai released GLM-5.2 the day after the US forced Anthropic to pull Fable 5 globally. A reaction: no-data is not good news, but the withdrawal is the lesson.</description>
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  <item>
    <title>Apple Silicon, MLX, and Core ML for on-device LLMs</title>
    <link>https://ai.jakubjirak.com/p/apple-mlx-coreml</link>
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    <pubDate>Sat, 13 Jun 2026 12:00:00 +0000</pubDate>
    <category>apple</category>
    <description>Unified memory made the Mac a serious local-inference box. MLX and Core ML are the two ways to actually use it — and they&#x27;re for different jobs.</description>
  </item>
  <item>
    <title>RAG that actually retrieves the right thing</title>
    <link>https://ai.jakubjirak.com/p/rag-that-retrieves</link>
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    <pubDate>Fri, 12 Jun 2026 12:00:00 +0000</pubDate>
    <category>rag</category>
    <description>Most RAG systems fail at retrieval, not generation. The fixes are unglamorous: chunk with intent, rerank, and evaluate the retriever on its own.</description>
  </item>
  <item>
    <title>Agentic architectures: the four topologies and where they break</title>
    <link>https://ai.jakubjirak.com/p/agentic-architecture-patterns</link>
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    <pubDate>Thu, 11 Jun 2026 12:00:00 +0000</pubDate>
    <category>agents</category>
    <description>Single agent, orchestrator-worker, evaluator loop, multi-agent. Most teams reach for the most complex one first. Here&#x27;s when each earns its keep.</description>
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  <item>
    <title>The architecture that cuts 99% of your LLM bill</title>
    <link>https://ai.jakubjirak.com/p/99-percent-cost-architecture</link>
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    <pubDate>Wed, 10 Jun 2026 12:00:00 +0000</pubDate>
    <category>cost</category>
    <description>Not one trick — five multiplicative levers. Cache, route, batch, compress, and shape output, and an order-of-magnitude bill becomes a rounding error.</description>
  </item>
  <item>
    <title>Stop burning tokens in GitHub Copilot</title>
    <link>https://ai.jakubjirak.com/p/copilot-token-diet</link>
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    <pubDate>Tue, 09 Jun 2026 12:00:00 +0000</pubDate>
    <category>copilot</category>
    <description>Premium requests, model pickers, and a chat that hoards context. A practical diet for getting Copilot&#x27;s value without torching your quota.</description>
  </item>
  <item>
    <title>Headroom: a compression layer between your agent and the model</title>
    <link>https://ai.jakubjirak.com/p/headroom</link>
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    <pubDate>Mon, 08 Jun 2026 12:00:00 +0000</pubDate>
    <category>tooling</category>
    <description>Tool outputs, logs, and RAG chunks are mostly filler. Headroom compresses them before they hit the model — 60–95% fewer tokens, accuracy preserved.</description>
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  <item>
    <title>Caveman: why use many token when few token do trick</title>
    <link>https://ai.jakubjirak.com/p/caveman</link>
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    <pubDate>Sun, 07 Jun 2026 12:00:00 +0000</pubDate>
    <category>tooling</category>
    <description>A skill that makes your agent talk like a caveman — drop filler, keep substance. ~65% fewer output tokens, and the accuracy often goes up, not down.</description>
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  <item>
    <title>Ponytail: the lazy senior dev inside your agent</title>
    <link>https://ai.jakubjirak.com/p/ponytail</link>
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    <pubDate>Sat, 06 Jun 2026 12:00:00 +0000</pubDate>
    <category>tooling</category>
    <description>He looks at your fifty lines, says nothing, replaces them with one. Ponytail forces the laziest solution that works — 80–94% less code, 47–77% cheaper.</description>
  </item>
  <item>
    <title>Stacking it all: ultra token savings at the same quality</title>
    <link>https://ai.jakubjirak.com/p/ultra-token-savings</link>
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    <pubDate>Fri, 05 Jun 2026 12:00:00 +0000</pubDate>
    <category>savings</category>
    <description>Caching, routing, compression, terse prose, lazy code. Wire all of them together and a real agent bill drops by an order of magnitude — without giving up output quality.</description>
  </item>
  <item>
    <title>Vibe coding, honestly: what changes when the agent writes the code</title>
    <link>https://ai.jakubjirak.com/p/vibe-coding-honestly</link>
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    <pubDate>Thu, 04 Jun 2026 12:00:00 +0000</pubDate>
    <category>vibecoding</category>
    <description>Strip the hype and &#x27;vibe coding&#x27; is a real workflow shift with a real set of new failure modes. What actually changes, what doesn&#x27;t, and why the harness beats the model.</description>
  </item>
  <item>
    <title>Sandboxing the agent: letting AI run code without losing the building</title>
    <link>https://ai.jakubjirak.com/p/sandboxing-coding-agents</link>
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    <pubDate>Wed, 03 Jun 2026 12:00:00 +0000</pubDate>
    <category>security</category>
    <description>An agent that can run a command can run the wrong command. Isolation, least privilege, and approval gates are the line between a teammate and an incident.</description>
  </item>
  <item>
    <title>Is a subscription the wrong business model for AI coding tools?</title>
    <link>https://ai.jakubjirak.com/p/subscription-wrong-for-ai</link>
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    <pubDate>Tue, 02 Jun 2026 12:00:00 +0000</pubDate>
    <category>economics</category>
    <description>Flat-rate pricing assumes a human-sized appetite for compute. Agents don&#x27;t have one. Why usage is eating subscriptions — and what pricing survives.</description>
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  <item>
    <title>Observability for agents: you can&#x27;t operate what you can&#x27;t see</title>
    <link>https://ai.jakubjirak.com/p/agent-observability</link>
    <guid isPermaLink="true">https://ai.jakubjirak.com/p/agent-observability</guid>
    <pubDate>Mon, 01 Jun 2026 12:00:00 +0000</pubDate>
    <category>observability</category>
    <description>A coding agent in production is a nondeterministic, multi-step, tool-calling system. Traces, token accounting, and eval dashboards are how you keep it honest.</description>
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  <item>
    <title>Governing skills at scale: progressive disclosure and software as memory</title>
    <link>https://ai.jakubjirak.com/p/governing-skills-at-scale</link>
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    <pubDate>Sun, 31 May 2026 12:00:00 +0000</pubDate>
    <category>skills</category>
    <description>Skills turn a general agent into a specialist. But a folder of prompts per developer is chaos. Central management, progressive disclosure, and institutional memory.</description>
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  <item>
    <title>Long-running autonomous agents: letting it work while you sleep</title>
    <link>https://ai.jakubjirak.com/p/long-running-autonomous-agents</link>
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    <pubDate>Sat, 30 May 2026 12:00:00 +0000</pubDate>
    <category>autonomy</category>
    <description>The frontier of agentic coding isn&#x27;t a smarter chat — it&#x27;s an agent you can trust to grind unattended for an hour. Budgets, checkpoints, and knowing when to walk away.</description>
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  <item>
    <title>Export controls and the geopolitics of your AI coding stack</title>
    <link>https://ai.jakubjirak.com/p/ai-export-controls</link>
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    <pubDate>Fri, 29 May 2026 12:00:00 +0000</pubDate>
    <category>policy</category>
    <description>The model behind your agent is also a geopolitical artifact. Export rules, open weights, and why where a model comes from is now an architecture decision.</description>
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  <item>
    <title>Knowledge graphs vs vector RAG: when relationships beat similarity</title>
    <link>https://ai.jakubjirak.com/p/knowledge-graphs-vs-rag</link>
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    <pubDate>Thu, 28 May 2026 12:00:00 +0000</pubDate>
    <category>rag</category>
    <description>Vector search finds chunks that look like your query. Some questions need chunks that are connected to each other. A practical comparison — and the hybrid that wins.</description>
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  <item>
    <title>Using AI to learn faster, not just to type faster</title>
    <link>https://ai.jakubjirak.com/p/ai-for-learning</link>
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    <pubDate>Wed, 27 May 2026 12:00:00 +0000</pubDate>
    <category>workflow</category>
    <description>The biggest gain from these tools isn&#x27;t the code they write — it&#x27;s how fast they get you to competence in something you didn&#x27;t understand yesterday. If you let them.</description>
  </item>
  <item>
    <title>Advanced agent architecture: context is the scarce resource</title>
    <link>https://ai.jakubjirak.com/p/advanced-agent-architecture</link>
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    <pubDate>Tue, 26 May 2026 12:00:00 +0000</pubDate>
    <category>architecture</category>
    <description>Past the basics, every hard agent problem is a context problem. Compaction, context editing, memory tiers, sub-agent isolation, and keeping intermediate results out of the window.</description>
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  <item>
    <title>Local-first, last-mile-paid: the model cascade that runs mostly free</title>
    <link>https://ai.jakubjirak.com/p/local-first-cascade</link>
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    <pubDate>Mon, 25 May 2026 12:00:00 +0000</pubDate>
    <category>cost</category>
    <description>Do the bulk of the work on a free local model; escalate to Haiku, then Sonnet, then Opus only at the last mile where it&#x27;s actually needed. The architecture and the triggers.</description>
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