Summer 2024

Conductor

Run a team of coding agents on your Mac

Visit website

What they do

runs a team of coding agents in isolated workspaces on a Mac

How close to us

5, very close

runs parallel coding agents with review and merge; same buyer as the coding wedge

Wedges

  • W1 Trusted 24/7 coding for small startup teams direct
  • W2 Seeing whether your AI agents actually produce adjacent
L1 Company brain (knows the organisation) 1, light
L2 Agent team (runs agents, tools, approvals) 3, strong
L3 Does and learns (finishes, checks, measures, updates the brain) 1, light

Who buys

Firm size
enterprise
Buyer type
developer
Role
individual engineer or engineering lead who adopts it; team admin buys the Teams plan
UK
not known
Their own description (from YC)

Run parallel agents in isolated workspaces. See at a glance what they’re working on, then review and merge their changes.

Full teardown

Conductor (YC Summer 2024): teardown vs XMarts

In one line: Conductor is an app where an engineer runs several AI coding agents at once, each in its own copy of the code, then reviews and merges their work [site] [docs]. Threat: 3 because it has the same buyer and problem as W1, is funded ($22M Series A, Mar 2026), is live, and names big-company users [blog] [yc]. It is a control room for agents, not a trusted overnight builder, so our answer must be about trust and learning, not about running agents in parallel.

1. Fact file

Item Finding Source
What they say Home page: "Run parallel coding agents on your Mac." YC line: "Run a team of coding agents on your Mac." [site] [yc]
Founded, team, funding Founded 2024, YC S24, San Francisco. YC lists 8 people. $22M Series A announced 30 Mar 2026, from Spark (Nabeel Hyatt) and Matrix (Ilya Sukhar, who also led the seed), with YC and founders of Notion and Linear; the post names no lead for the Series A. A $24M total is UNVERIFIED: the press piece found says $22M and no source gives a cumulative total. [yc] [blog] [press]
Founders Charlie Holtz (CEO): led growth at Replicate, ex-quant developer at Point72, Brown. Jackson de Campos (CTO per one profile): met Charlie at Brown, ex-Netflix. What YC likely saw: a founder with a past hit tool (Charlie built Chorus, a multi-model chat app: UNVERIFIED, the podcast page does not mention it) plus a strong engineer (inference). [yc] [jobs] [press]
Customers They claim "dozens of engineers" at each of Google, Meta, HubSpot, Chime, Intercom, Ramp, Datadog, Block, Flexport, Rippling, Amazon and Spotify. They claim YC startups write 100% of their code in it. The job ad names engineers at Linear, Vercel, Notion, Stripe and YC as users. No named case study with a number. [blog] [jobs]
Price Public. Free; Pro $50 a month; Teams $60 per user per month; Enterprise custom. Cloud workspaces carry no extra fee now; usage pricing for cloud compute is planned. Users bring their own model subscriptions or keys. [site]
Path Mac app launched about mid-2025 [press]. Series A 30 Mar 2026 [blog]. cmd (Xcode AI tool, founder Guillaume Sabran) joined 2 Apr 2026 [blog]. Conductor Cloud, API and iPhone beta 30 Jul 2026 [press]. iPhone app v1.0 14 Sep 2026 [press]. Sign in with ChatGPT 29 Sep 2026 [blog]. YC's data lists the former names BookMe, Melty and Chorus; I could not confirm the renames on the public web (UNVERIFIED) [yc]. as tagged

2. Their proposition, reverse engineered

Part What they do
Who buys Individual engineers first (free tier, bring your own subscription), then teams (Teams plan) and big companies (Enterprise) [site]. Bottom-up adoption (inference from the free tier and the user claims).
The pain One agent at a time is slow. Many agents at once make a mess of files and branches, and you lose track of who is doing what [docs] (inference on "the pain": the site does not state it in the buyer's words).
The promise Run many agents in parallel, see at a glance what each is doing, then review and merge [yc].
How it works Each task gets its own workspace, branch, files, terminal and diff [docs]. Works with Claude Code, Codex, Cursor and OpenCode [docs]. Since Jul 2026 workspaces can run in the cloud in shared microVMs and keep going when the laptop is closed [press]. Other people can watch and steer a workspace (multiplayer) [site] [press]. An API lets other tools, and agents, start workspaces [press].
The output A reviewed diff, a pull request and a merge. A kept session so a teammate need not rebuild context from the PR [press].
Proof style Growth and logos: "10x" user growth Jan to Mar 2026 and a list of big firms [blog]. No revenue, no hours saved, no bug counts.
Who sells it Self-serve download, plus "Reach out" for Enterprise [site]. The 3 open jobs are all engineering, none in sales [jobs].
Price model Per seat, $0 / $50 / $60 a month, plus custom enterprise [site].
The story Their enemy is working alone with one agent and the old way of coding. Their belief: "Code is almost like the sawdust of the conversation." The conversation is the lasting thing, and agents will become the main users [press]. Mission in the job ad: "the human interface to AI organizations" (their words, paraphrased) [jobs].

3. Positioning

  • Category they claim: "first AI orchestrator" and the human interface to AI organizations [jobs]. The site calls it the best way to run multiple coding agents in parallel [site].
  • Category a YC partner would put them in: developer tooling for coding agents, a control plane or workbench over Claude Code and Codex (inference).
  • What they want to be known for: the place where teams assign and supervise coding agents, with model vendors supplying the intelligence [press].
  • Where they sit on the map: L1/L2/L3 = 1/3/1, buyer = enterprise by named customers, developer-led adoption.

4. Three layers vs ours

Layer Them (score + evidence) Us (Marton's logs show)
L1 Company brain 1. Keeps session context so a teammate can pick up a workspace [press]. No company-wide memory of decisions, rules or goals found; docs page does not mention shared context files, memory or learning [docs]. A vault of about 1,400 pages, 112 call transcripts and about 8,700 customer quotes, searchable by meaning.
L2 Agent orchestration 3. Running and watching many agents is the whole product [site]. Agents can start their own workspaces through the API (shown as a demo) [press]. A human approves by review and merge. Agents come from other makers; Conductor does not build its own [site]. About 5,600 jobs run by agents from three makers, a queue across three Macs, each job built in its own copy of the code.
L3 Execution and learning 1. The agents do the work, and Conductor shows the diff, PR and merge steps [docs]. A "checks" page exists in the docs, but no measuring of results and nothing fed back to improve the next run was found [docs] (inference: screen shows status, does not learn). Each job is checked by a different AI, then automatic tests. About 160 failure records, each with an automatic check. Only about 15% of jobs reached the main code, and merges were unreliable in October.

5. Same and different

Topic Same or different Them Us
Core idea Same Many coding agents in parallel, each isolated, work reviewed then merged [docs]. Marton's logs show a queue where each job is built in its own copy of the code and merged only after checks.
Engines Same Claude Code, Codex, Cursor, OpenCode [docs]. Marton's logs show Codex, Claude and Gemini engines.
Buyer Same Engineers and engineering teams; startups and big firms [blog] [jobs]. W1 targets small startup teams (brief). No customer yet.
Who does the checking Different A human reads the diff. Charlie says he looks at code less over time [press]. Marton's logs show a different AI reviews every job before the automatic tests.
Learning Different Not found. Context travels with a session; no rules learned from accepted or rejected work [press] (inference from absence). Marton's logs show a failure record plus an automatic check for each failure, and offer-feedback lines fell from 44 to 18 on one workflow.
Where it runs Different Mac app, now cloud microVMs and an iPhone app [press]. Marton's logs show it runs on three Macs of one person, with absolute paths. Not yet usable by others.
Size and speed to start Different Download, free tier, bring your own subscription [site]. First value in minutes (inference). Needs set-up by Marton; not self-serve.
Proof Different Logos and 10x user growth, all their claims [blog]. No outside customer. Numbers are from our own system.
Price Different $0 / $50 / $60 per user a month [site]. Not set.

6. Wedge overlap

Wedge Fit Why
W1 Trusted 24/7 coding for small startup teams direct Same buyer (engineers at startups), same job (get more done with many agents). Their cloud workspaces now keep agents running with the laptop closed [press]. They are the crowded centre of W1.
W2 Seeing whether your AI agents produce adjacent They show what each agent is working on [yc]. No cost view, stuck-job alert or silent-failure check found [site] [docs] (UNVERIFIED that none exists). Covers only agents run inside Conductor.

7. Whitespace (where they stop)

  • Layer gap: no company brain and no learning from results [docs] (inference). To own it we need a rule-change log tied to checked runs, with rework falling over weeks. This is the W1 plus W8 angle in the brief.
  • Buyer gap: they build for engineers. Nothing is aimed at a finance or operations leader who wants a result owned [site]. Also unknown in the UK: SF office only on the job ad [jobs]. To own it we need a non-engineer buyer or a UK team saying they have the pain.
  • Number gap: public proof is logos and growth, with no hours saved, bugs avoided or revenue [blog]. To own it we need one workflow with a before/after number (merged changes per week, rework rate, hours).
  • Price gap: not a gap. $50 and $60 a seat is cheap, and the base is free [site].
  • Speed gap: not a gap. Download and run [site].

8. For the YC application

  • Proven today: Marton's logs show his system runs agents from three makers around the clock: about 5,600 jobs, each built in its own copy of the code and checked by a different AI, then automatic tests. About 160 failure records each added an automatic check. This is on his own business only, and about 15% of jobs reached the main code.
  • Draft answer to "how are you different from Conductor?": DRAFT. "Conductor is a window where a person runs and reviews coding agents. Our system already runs a queue of agents day and night, has a different AI check every job, and turns each failure into an automatic check, on our own business." Founders say it their own way.
  • Future claim (needs proof): "Our agent team gets better with every accepted or rejected change, so you review less over time." Needs one outside team using the system for 4+ weeks, with a rework rate or review time that falls.
  • What we understand that they don't: the limit on agent work is trust in what comes back, not the number of agents you can run. needs proof; Marton's logs show it on his own system (failures are named and each gets a check), but no outside team has used it.
  • Copyability (M3): easy. They already ship code review, routines (automation), an API, an MCP server and cloud workspaces [changelog]. An automatic review step is a feature for them, and it fits their engineer buyer. They have $22M and an 8-person team that ships regularly (two releases in the first half of Oct 2026: 0.90.0 on 2 Oct and 0.91.0 on 15 Oct) [blog] [changelog]. A learning loop across runs is harder (medium), but nothing blocks them. Not hard, so M3 can not score above 3 against Conductor.
  • Why now (M4): None found in this teardown. Do not use "agents run for hours now": that is general AI progress. (Their own risk, not our edge: Anthropic announced subscription changes for third-party Agent SDK tools on 13 May 2026 and delayed them on 15 Jun 2026 [blog].)
  • Do not claim: that our system is "trusted" or "24/7 reliable" (landing was unreliable in October; Marton's logs show 15% of jobs merged). That anyone but Marton has used it. That Conductor lacks review, cloud or API (it has all three). "Parallel agents" as our headline (it is their product).

9. Ideas worth taking

  1. A mobile app to review and merge, because Slack is "too noisy" for agent work [press]. A leader can approve from a phone.
  2. Hand over the session, not just the diff, so a teammate keeps the context [press].
  3. An API so other tools and agents can start work, which makes the product a base others build on [press].

10. Unknowns

  • Revenue, paying seats and how many of the claimed logos are paid teams. Look for a later funding post, a podcast or a talk.
  • What the enterprise page really offers; the fetched text showed no features or logos [site]. Check the rendered page.
  • Whether the renames (BookMe, Melty, Chorus) are real and how they link to Conductor. Ask the founders or check old launch posts.
  • UK or EU customers. Look at the customer logos and any careers page outside the SF job ads.
  • Whether "routines" (automation, v0.85.0) can chain work or learn from results. Read the docs page for routines.
  • Whether the "checks" doc page measures anything beyond CI status.

Sources

Technical detail
Slug
conductor
Lens hash
179096c479
Pass
deep
Stale
no