Thought for 2.1s
Starting with the queue and the error tracker before I touch anything.
Agent infrastructure to enable the right harness, model, and context for every task.
import { Checkfu } from "@checkfu/sdk"const checkfu = new Checkfu({ apiKey: process.env.CHECKFU_API_KEY!,})// 01 Create specialized architect and coding agents on different harnessesconst architect = await checkfu.agents.create({ name: "lead-architect", harness: "claude-code", model: "claude-opus-5", system: "Plan refactors, enforce architectural invariants, and review PR diffs.", tools: [{ type: "agent_toolset_20260401" }],})const coder = await checkfu.agents.create({ name: "code-executor", harness: "codex", model: "gpt-5", system: "Execute code modifications inside the sandbox and verify unit tests.", tools: [{ type: "agent_toolset_20260401" }],})Choosing the right model is only part of the equation. Pairing it with the right harness, context, and taste is what makes an agent actually work.
Some agents need a real computer with a browser that stays up for days. Others need a fresh sandbox for one second of code. Pick per agent. The agent loop runs apart from the machine, so a lost worker never loses the session.
A worker can die mid-command. The run keeps going, and the result lands once.
A desktop, a browser, and files that stay put for days.
Fresh compute in under a second. Run one job, then throw it away.
Give your agents the exact context they need to act accurately. Stage Git repositories, stream files into the filesystem, retain cross-session memory, and load modular skills.
Each agent mounts only what its job needs.
Equip your agents with hundreds of tools across communication, code, research, data, and business automation — with vaulted OAuth, credential encryption, and human approval gates.
Team chat, workspaces, calendar schedules, and email automation.
Issue tracking, design tokens, error monitoring, and code repositories.
Deep research, web crawling, neural search, and live browsers.
Cloud databases, serverless platforms, edge compute, and metrics.
Payments, CRM pipelines, storefront orders, and workflow triggers.
And hundreds more through MCP & REST
Checkfu natively speaks the Model Context Protocol. Connect any custom MCP server, OpenAPI endpoint, or private microservice with zero protocol boilerplate.
Deploy agents directly into team chat channels or connect via API. Every turn, tool call, and state transition is written to an append-only event ledger that survives crashes and exports to JSON.
Thought for 2.1s
Starting with the queue and the error tracker before I touch anything.
Thought for 3.4s
runner-11 claimed all three jobs at 02:10 and stopped heartbeating at 02:14, but its claim was never released, so the queue still counts the jobs as in flight. Confirming from the runner itself.
Thought for 4.0s
Root cause: a stale claim from a dead runner, not a bug in the export itself. Releasing the claim and requeuing the three jobs is a write against production, so it needs a human.
Thought for 1.8s
Found it, and it’s moving.
What happened. runner-11 claimed Acme’s three export jobs at 02:10, stopped heartbeating at 02:14 (Sentry EXPORT-412), and its claim was never released, so the queue kept treating the jobs as in flight. The export itself is fine.
What I did. With maya’s approval I released the claims and requeued the three jobs. One has completed, one is running, and the last should land in about ten minutes. I posted the same update in the #support thread for the CSM.
I wrote the diagnosis to the support runbook under exports/stuck-queued, so next time this is a one-query check.
Reply in the thread if the CSM needs a written incident note.
Session
Run
Cost
From coding orchestrators and personal assistants to team coworkers and autonomous agents, build what’s next on Checkfu.
fix-flaky-tests
cloud+9 −3
bump-deps
local+41 −41
migrate-api
cloud+212 −87
rename-config
local
local runner
CI is flaky on the payments suite. Find the leak and fix it.
running vitest --retry 2
3 failed, isolating test order
patch applied to test/setup.ts
412 passed, opening summary
A shared fixture leaked between files. Reset it per test; suite is green.
test/setup.ts+8 −2
vitest.config.ts+1 −1
Fleets of parallel coding agents running inside isolated cloud microVMs with git worktrees and automated pull request generation.
A 24/7 personal executive assistant with long-term memory, daily schedule triage, and proactive morning briefs.
Today 8:52
Delivered
7:00 · automation morning-brief
Chats
Tasks
Projects
recent
Checkout spec → issues
Refund policy audit
Launch handbook refresh
Turn the checkout Figma spec into Linear issues and post them to the launch channel.
read figma:checkout-v3 · 12 frames
drafted 4 issues with acceptance criteria
create 4 issues in linear:acme — decide in Checkfu
created LIN-231 … LIN-234
posted summary in #launch
In-channel teammates collaborating with engineering and product teams inside shared Slack and Discord threads.
Autonomous back-office agents classifying compliance documents, auditing risk factors, and tagging files in enterprise vaults.
Acme Corp ▾
channels
# compliance
# legal-ops
# vendor-risk
apps
Fizz
priya9:02
FizzAPP9:02
acme-msa.pdfConfidential2 fields masked
northwind-nda.pdfInternalclean
globex-dpa.pdfRestricted6 fields masked
Tagged 14 files in box:legal-vault · audit trail written
Track today’s discussion of agent harnesses. Verify anything surprising, then draft a thread.
On it. Honey scouts, Fizz verifies. I’ll only pull you in for a yes.
MessagedHoney· 14 messages
Honey found three threads. The surprising one claims swapping harness mid-session drops tool state. Handing it to Fizz.
MessagedFizz· 11 messages
Fizz reproduced it: real on one harness, fixed this morning. Draft thread is ready with both links. Post it?
yes, post it
Posted. Honey keeps watching; next pass in 15 minutes.
Bumble’s screen
Routines
A crew of lightweight bots you message like contacts: each created in a line, each with its own durable computer, talking to each other through a coordinator, and reachable by anyone else’s bot over A2A.
Focus on what differentiates your product experience with the right choice of model, harness, context, and taste.
Survive crashes and resume runs from the event log.
Isolated cloud or local compute decoupled from the loop.
Stage Git repos and files with zero app-side git.
Vaulted tokens with auto-refresh. Secrets stay hidden.
Personal vs. workspace scopes with human ActionApprovals.
Call MCP tools and APIs without custom protocol glue.
Proactive runs triggered by schedules and webhooks.
Scoped memory stores that auto-update from sessions.
Bind Slack and Telegram threads with delivery queues.
Coordinators delegating tasks to subagent teams.
Grade runs against success rubrics before closing.
Versioned prompts and scripts agents load on demand.
Pick the harness and model. Checkfu runs everything around them.