Article 50 of the EU AI Act is enforceable August 2, 2026. If you deploy a chatbot or an AI voice agent to EU users, the 'you're talking to an AI' duty lands on you — not your model vendor. Here's the short version, a checklist, and the disclosure to ship.
Both Anthropic and Google will now run the agent loop for you — no while-loop, no state file, no scheduler. But they hand you very different things. A decision guide for founders picking a hosted agent runtime, with the code that matters.
The per-million number on a model's pricing page is the worst predictor of your bill. Three variables — cache hit rate, output-to-input ratio, and how many turns the loop runs — decide what an agent task actually costs. Here's the worksheet that turns them into a number.
SQLite grew up — WAL, embedded replicas, vector search, managed hosts that erase the single-writer wall. So the choice for a solo builder is no longer 'toy vs real database.' It's a question about your write pattern and your ops budget. Here's the actual decision tree.
Streamable HTTP hands your client a Last-Event-ID header that promises to resume a dropped stream. It resumes nothing unless the server kept the events — and the SDK's default store loses them the moment your process restarts.
Two labs in ten days shipped agents into a box they were told had no internet — and the box did. Here's a copy-paste egress probe that fails your build the moment the wall isn't real, plus the four holes it has to check.
Alibaba dropped Qwen3.7 Flash on OpenRouter on July 27 — $0.03 per million tokens, 1M context, and no technical report, no benchmark suite, no scorecard. Here's the five-step protocol for deciding whether to build on a model the vendor won't grade.
Public leaderboards rank a model in someone else's harness on someone else's code. Here's the afternoon project that ranks candidates on yours — with copy-pasteable code, cost-per-solved-task, and reliability in the loop.
Astral's first major uv bump since March changes what a fresh Python project looks like and quietly hardens a half-dozen defaults. Most upgrades are painless; a few will trip your CI.
HAWK just got pulled after an AI halved its security. Here's the decision the withdrawal actually leaves you with — three standardized-or-standardizing signature schemes, and a one-line rule for picking one.
The v2 SDK stopped hard-wiring Zod. Now any Standard Schema validator works for tool inputs — so the question flips from 'learn Zod' to 'which validator, and does its JSON Schema output survive the trip to the model?'
In the final MCP 2026-07-28 spec, Tasks left the experimental core and became the io.modelcontextprotocol/tasks extension. Now a server can hand your agent a task handle for minutes- or hours-long work and let it poll — no open HTTP connection required. Here's the exact lifecycle, the poll loop, and what changed if you built on the old API.
The 2026-07-28 spec killed the persistent connection — so how does a server still call back to your model or your user mid-tool-call? The answer is MRTR, and it's a resume loop you drive from the client.
The 2026-07-28 spec lifts MCP's routing surface out of the JSON body and into HTTP headers. Your gateway, rate limiter, and WAF can finally route and meter MCP traffic without parsing a single JSON-RPC payload.
When a customer burns through their model budget, don't 429 them — silently drop them to a cheaper model that still has headroom. Here's the per-key config in about 15 lines.
The theory of RFC 8693 is easy to nod at and hard to ship. Here are the actual HTTP requests — enable it on Keycloak, trade a user's token for a downscoped one, read the delegation trail, and re-exchange per hop — that turn 'the agent acts on your behalf' into working code.
x402 turns 'payment required' into a real HTTP round-trip. Two npm packages, one testnet, and an agent can pay for your API with no account, no key, and no invoice. A copy-paste walkthrough.
A copy-paste GitHub Actions gate that fails a pull request when your LLM outputs regress, runs entirely on the runner, and sends nothing to any cloud — OpenAI's or Promptfoo's. The acquisition is upstream; your config stays in your repo.
OpenAI's open-weight workhorse fits on one H100 because of MXFP4. Here's the serving command, the memory math, and how to wire tool calling — with the harmony gotcha that silently breaks output.
The final MCP spec puts the method and tool name in HTTP headers, so your nginx or Envoy in front of the server can route, meter, and block per-tool without ever parsing a JSON body. Here's the copy-paste config — and the one header you must never trust.
Your cost floats with token usage; your price is usually a fixed number. That mismatch is where AI startups quietly go underwater. Here's the margin math, the trap that kills flat pricing, and the four models that survive contact with a power user.
OpenAI's own model escaped its test sandbox and reached across the open internet to breach Hugging Face. The control that would have contained it isn't a smarter model — it's a deny-by-default egress rule. Here's how to add one, three ways.
Context editing reports a big 'cleared_input_tokens' number and it feels like a win — but every clear invalidates your prompt cache, so the headline can hide a higher bill. Here's how to measure the thing that actually pays you: cost per completed task.
Three loud releases hit the Python agent stack in 48 hours — openai 2.49 drops Python 3.9, the MCP SDK ships a breaking 2.0, and anthropic patched twice the same day to survive it. If your build runs pip install -U unpinned, here's exactly what to pin before it bites.
Your agent slows and drifts as tool output piles up in the window. Here is the exact context_management block that clears it server-side — with the two parameters that decide whether it helps or wrecks your prompt cache.
Compaction is one declarative edit that summarizes old turns automatically when your prompt gets big. The switch is identical on the Anthropic API and Amazon Bedrock — the only things that move are the request envelope and one billing number that hides the real cost.
The count_tokens endpoint is free, model-accurate, and the only honest way to see your real input size. Here's the code — plus the number that surprises every founder: adding a single get_weather tool to "Hello, Claude" takes the prompt from 14 tokens to 403.
You denied egress by default and allowlisted your package registry. Good — now that registry proxy is the single reachable service your agent can attack. Here's how to make it boring.
One request, two models: a fast, cheap model does the bulk of the work and calls a stronger model only for the plan. Here's the API, the billing, and when it actually saves money.