Agent Budget Exhausted Halfway Through the Task
Your agent burns through its token or cost budget before finishing, leaving work incomplete. Here's how to diagnose spending and resume safely.
Articles tagged with #AI coding
Your agent burns through its token or cost budget before finishing, leaving work incomplete. Here's how to diagnose spending and resume safely.
Your agent resumes from a checkpoint but the state is garbled, missing fields, or internally inconsistent. Here's how to detect corruption and recover safely.
Your pipeline's cost report shows $2 but the invoice says $18. Sub-agent token usage is not attributed to the parent run. Here's how to close the gap.
Agents call each other in a loop that never terminates because the orchestrator has no cycle detection. Here's how to find cycles before they run forever.
Your multi-agent pipeline drops critical context at handoff boundaries. Learn to identify the gap and wire durable state in under an hour.
Two agents block forever waiting for each other's output — a classic deadlock in async pipelines. Detect the cycle and break it in minutes.
API keys, tokens, and passwords in agent output get written to logs and traces. Here's how to detect secret leakage and scrub it before it reaches storage.
Your agent wraps JSON in markdown or adds prose commentary, breaking the downstream parser. Here's how to enforce structured output reliably.
Your agent proceeded without running required pre-flight checks, causing avoidable failures downstream. Here's how to enforce mandatory checks before execution.
Your agent pipeline promotes flawed outputs because gate criteria are too broad or easy to satisfy. Here's how to tighten gates without over-blocking.
Different versions of your agent use subtly different prompts, causing inconsistent output across the fleet. Here's how to version prompts and detect drift early.
A single rate-limited agent stalls the entire pipeline as upstream agents queue and timeout. Learn to isolate rate limits and prevent cascade failures.
One unreliable tool call causes your agent to retry hundreds of times, exhausting budget and rate limits. Here's how to add backoff and circuit-breaking.
Two agents write to the same shared memory store simultaneously, producing garbled or inconsistent state. Here's how to detect and prevent overlapping writes.
Your agent bypassed a critical validation gate and pushed bad output downstream. Learn to enforce non-skippable checkpoints in any agent pipeline.
After a crash or restart, your agent believes the world is in a state that no longer matches reality. Here's how to detect drift and resync reliably.
Subprocesses launched by your agent keep running after the agent exits, consuming resources and causing side effects. Here's how to track and clean them up.
Your orchestrator sends tasks to the wrong specialist agent, producing garbage output. Here's how to diagnose routing logic and fix misclassification.
Your agent trace shows a result but no corresponding tool call, hiding what actually happened. Here's how to find the gap and make traces complete.
Parallel agents overwrite each other's changes, causing lost edits and broken code. Here's how to detect conflicts and enforce file-level locking.
Turn git log into release notes that aren't just a dump of commit messages.
The three things AI gets wrong on migrations: reversibility, backfill, and the NOT NULL on a big table.
Use AI to draft incident postmortems fast, without losing the uncomfortable truths.
AI can resolve most merge conflicts safely. Knowing which ones are NOT safe is the workflow.
How to use AI when you get paged at 3am — triage, hypothesize, calm down protocol, capture as runbook.
Turn a git diff into a PR body a reviewer will actually read, with prompts that don't invent test plans for tests that don't exist.
Pip install, point it at a repo, and run the see-diff/accept loop from your shell — no IDE, no browser, no lock-in.
What MCP is, how to add a server with claude mcp add, three transport types, and the first servers worth installing.
Rules anatomy, when to use .cursor/rules/*.mdc vs the legacy .cursorrules, and how to write rules the model actually follows.
Codeium's AI-first IDE walkthrough — install, configure, and run the first Cascade agent task without fighting the tool.
You hit Cmd-K, type the change, and the inline popup spins forever. No diff, no commit, no error. Usually network, model, or context. Walk the four root causes.
AI registered a new endpoint outside the authenticated route group, exposing internal data without checks. Detect the gap and enforce auth as a default.
AI confidently calls a method that does not exist — wrong arg order, made-up option name, fabricated return type. Diagnose by pinning to real source.
AI-written migration runs clean on an empty dev DB but blows up on prod with constraint or data errors. Fix with dev-prod parity and safety checks.
AI wrote a query or update that holds long locks on a production table, blocking reads and writes. Identify the pattern and rewrite it to be lock-friendly.
AI generates code with deprecated APIs, fixes one lint error, then re-introduces the same pattern in the next file. Pin the rule and ground the prompt.
AI runs npm install and creates package-lock.json in a pnpm-only repo, breaking the lockfile invariant. Pin the manager and lock the rules.
Cursor's Auto model router routes a complex refactor to a small model, producing shallow or wrong edits. Diagnose routing signals and force the right model for hard tasks.
Cursor picks the system Python instead of your project venv, breaking imports, linting, and agent-generated code. Diagnose the interpreter picker, venv discovery, and shell PATH.
Cursor Settings Sync pushes outdated config to a second machine, clobbering local rules, keybindings, or MCP servers. Diagnose conflict direction, last-write-wins, and selective sync.
Cursor's SSH Remote session disconnects while you are editing, losing the agent context and unsaved buffer state. Diagnose the keepalive, network, and remote extension host.
Codex ran git commit on whatever branch was checked out — sometimes main, sometimes a leftover branch from the previous task. How to force a clean per-task branch.
Codex's PR is green in CI — every test passes — but the app crashes in staging. Why agent fixes that target the test surface miss the runtime, and how to close the gap.
A complete Codex keyboard shortcut reference for the terminal TUI, desktop app, input editing, session control, mode switching, background tasks, and failure cases.
A complete Codex skills guide: what a skill is, how /skills discovery works, how to invoke skills, how to write SKILL.md, and how built-in, plugin, and custom skills differ.
You asked for a library, it gave one that's been abandoned 4 years — training cutoff + no registry check.
All green, ship it, prod breaks — tests covered the happy path only, mocks shielded real branches.
Autocomplete predicts the next 20 lines from local context; agents plan across files. Use this decision rule to map task shape to the right mode.
Use AI to pre-review your site against AdSense common rejection causes before applying.
Use Claude Code, Codex, or Cursor agents to pre-review your own PRs before sending them to humans.
Use AI to challenge your architecture decisions before you commit weeks of code.
A repeatable AI audit workflow for Astro content sites — catches broken slugs, missing translations, dead internal links, draft leakage, and config drift.
Astro-specific audit prompts — sitemap, hreflang, output mode, RSS.
AI can flag common React Native issues — re-renders, navigation, native modules.
A monthly workflow to surface broken internal + external links using AI + simple tooling.
Category pages are an under-audited SEO surface — this AI workflow catches duplicate intros, weak internal linking, missing descriptions, and bad pagination.
Use Claude Code, Cursor, or ChatGPT to give yourself a guided tour of an unfamiliar codebase.
AI coding quality is mostly a context problem. Here is how to feed agents the right context — and not the wrong one.
Use AI to identify pillars, cluster topics, and content gaps for your niche.
A reproducible workflow for debugging with AI that doesn't spiral into 20 wrong guesses.
Use Claude Code or Cursor to upgrade dependencies without breaking the build in subtle ways.
Pre-flight checks via AI — firebase.json correctness, rewrites, function regions.
Build a content site with AI assistance — content + structure + SEO.
Use AI to audit hreflang implementation — slug mismatches, missing pairs, wrong codes.
Use AI to write meta descriptions at scale — without losing the quality that matters.
A structured prompt workflow for big migrations: Vue 2→3, React class→hooks, JS→TS, Pages Router → App Router.
AI agents in monorepos either work great or melt down. Here is how to set them up to work.
A 60-second review pass with an AI agent before every commit. Catches the dumb stuff before it leaks.
Refactoring with AI works when tests exist and scope is small.
Don't fear letting AI edit — fear losing the ability to undo.
A weekly 30-min AI workflow to triage Search Console: index coverage, Core Web Vitals, mobile usability, manual actions.
Turn a written feature spec into shipped code without the half-built-feature trap.
Skip the generic 80-point SEO checklist. Generate one tailored to your stack (Astro / Next / Hugo / WordPress) with AI in 20 minutes.
AI-generated tests often pass while testing nothing. Here is a workflow that gives you real coverage.
A 3-pass AI workflow that scores every page for thin content, surfaces the worst offenders, and proposes one of: expand, merge, noindex, delete.
Use AI to audit a project for security, performance, and UX gotchas.
Have AI surface likely bug spots in a module before they cause incidents.
ChatGPT is not Claude Code, but used right it still ships real features. Here is how.
What Claude Code is, how to install it, and how to ship your first refactor — the setup steps, prompt patterns, and common beginner mistakes.
CLAUDE.md isn't just a readme — it's your agent's memory. Here's what to put in it.
A reusable Claude Code prompt + workflow to run a real SEO audit on your content site.
What Codex does, how it runs sandboxed cloud tasks, and when to use it. Setup, the spin-off workflow, and the mistakes that bite first-time users.
Use Codex as a pre-review pair — catches issues before humans see them.
Use Codex to spot-check sitemap correctness, freshness, and coverage.
Goal + constraints + acceptance criteria. Skip any and the AI guesses.
Cursor's real learning curve isn't install — it's knowing when to use Tab, Inline edit, Composer, Chat, or Agent. Four real edits, one per AI surface, in an hour.
A well-tuned index is the difference between Cursor "getting" your code and not.
A 30-page audit dumped into chat produces vague edits. Use this chunk-summarize-prioritize pattern to turn long reports into a brief the agent can execute.
Gemini's coding has improved fast. Honest take on where it earns the click and where to switch to Claude or ChatGPT.
Commit messages, commit boundaries, and what NOT to let AI commit.
A 200-line diff isn't safe just because it compiles. Read it like a senior would.
Use Cursor + Claude Code + Codex together - without conflicts.
AI sometimes touches what it shouldn't. Guardrails that actually work.
Use AI to audit your site's SEO basics - titles, descriptions, structured data, internal links.
Agent keeps trying the same fix or oscillates between two states. Break the loop fast.
Classic case: AI added a dep without committing the lockfile, or relied on a local Node version.
After an AI run, npm run build fails. Diagnose with diff review, type-checking, and selective revert.
Agent rewrote .env with placeholders or removed entries — recover and prevent.
Agent imports `src/utils/superhelper.ts` that was never created — common, fixable.
Your branch + AI edits conflict with main. Resolve without losing AI improvements.
Agent ran an install or removed deps and now your lockfile is at war with the team's.
Agent created `UserList2.tsx` next to the original or scattered duplicates. How to clean up safely.
AI "simplified" code and quietly removed a branch your users actually rely on.
Three commands cover 99% of rollback scenarios: stash, restore, reflog.
AI produces code that doesn't type-check — usually wrong types, any-casts, or missing generic parameters.
Claude Code editing the wrong files, duplicating existing functions, missing key files? It's almost never the model — it's missing project context. Seven ways to make Claude Code actually read your codebase.
Codex creates files in the wrong place or with wrong conventions — constrain with AGENTS.md and explicit refs.
Cursor shows edits but Apply does nothing or fails silently.
Cursor edits only what it can "see" — fix by adjusting indexing scope and explicit @file references.
Cursor pulls in old / vendored / generated files into context. Fix the index and ignore lists.
You committed over what you wanted to keep. Three paths back. Usual causes: accidental commit overwrite; hard reset moved head. Start with: `git log -p -- <file>` to see the file's history.
A 200-line AI diff isn't safe just because it compiles. Read it in the right order.
Two agents (Cursor + Claude Code) edited the same file. Merge cleanly, don't panic.
12 prompts that walk a page like a keyboard-only and screen-reader user — semantics, focus, ARIA widgets, contrast, modal stacks, live regions, WCAG mapping.
15 prompts that pressure-test REST and GraphQL contracts before they ship — naming, status codes, error model, breaking changes, pagination, N+1, field-level auth.
13 prompts to systematically hunt hidden bugs in code before they ship.
12 prompts to brief Claude Code (or Codex) on real engineering tasks — scoped features, surgical bug fixes, migrations, refactors, TDD, perf work, debugging, code review.
13 prompts for AI code review that surfaces real issues — bugs, security, performance, readability, tests.
12 prompts that walk a schema like a future migrator — normalization, indexes, FK cascades, nullability, soft-delete, JSON columns, migration safety, ORM diff.
12 prompts to pre-flight your deployment — env vars, DNS, cache, observability, rollback drill, post-launch monitoring, security headers, status page comms.
13 prompts for performance work that actually moves a number — measure-first bottleneck ID, LCP / CLS / N+1 / TTFB / bundle / cache fixes, before-after Web Vitals diffs, and a premature-optimization detector.
13 prompts to refactor React components — extract hooks, lift state, split server vs client, memoize correctly, kill prop-drilling.
12 prompts for READMEs that get a new reader from git clone to a working install in 60 seconds — skeleton, quickstart, install troubleshooting, examples, API reference, and audit.
18 copy-ready prompts to plan, execute, and verify AI refactors without breaking behavior — module extraction, renames, async migrations, and god-function splits.
12 prompts to AI-audit your code for OWASP-grade security issues — auth, authz, secrets, deps, file uploads, CORS, PII logging — without hiring a pentester.
12 prompts to AI-audit a content site — metadata, internal links, hreflang, thin content, canonical, schema, cannibalization, Core Web Vitals — with measurable thresholds and fixes.
13 prompts for integration, E2E, snapshot, and contract tests — for unit-test prompts specifically, see the unit-test article. Tests that catch real bugs, not noise.
14 prompts to diagnose TypeScript errors fast — generics, conditional types, narrowing, module resolution, declaration files.
Claude Code is a terminal agent; Cursor is an in-editor copilot. Task fit, debug loop, and rollback cost differ. A decision sheet.
From install to your first useful edit in 30 minutes: Inline vs Composer vs Chat, codebase indexing, @Files context injection, Apply, and rollback.
Cursor stuck on Indexing? 90% of the time it's trying to index node_modules, dist, .next, or cache directories. Here's the .cursorignore template and a clean rebuild flow.
OpenAI Codex and Anthropic Claude Code are both AI coding agents — but they live in different places and solve slightly different problems. Here's a clear comparison.
Claude Code is Anthropic's command-line AI tool. This guide explains what it does, how it differs from ChatGPT and Cursor, and how to get productive in the first ten minutes.