Fall 2025

Amika

Infra to build your own software factory

Visit website

What they do

sandboxed cloud coding agents that ship pull requests for engineering teams

How close to us

5, very close

runs autonomous coding agents for startup-style teams, same problem as W1; no measured learning shown

Wedges

  • W1 Trusted 24/7 coding for small startup teams direct
  • W2 Seeing whether your AI agents actually produce adjacent
  • W8 The other 90% of an AI skill adjacent
L1 Company brain (knows the organisation) 1, light
L2 Agent team (runs agents, tools, approvals) 2, clear
L3 Does and learns (finishes, checks, measures, updates the brain) 1, light

Who buys

Firm size
sme
Buyer type
developer
Role
head of engineering or founding engineer
UK
not known
Their own description (from YC)

Amika is infra to build your software factory.

We give your team sandboxed AI coding agents in the cloud: the same infrastructure Ramp, Coinbase, and Stripe built in-house. Kick off work from a web UI, CLI, Slack, or API. Use your preferred coding agent (Claude Code, Codex, etc.). Each agent understands your codebase, runs autonomously, and ships real PRs with live previews of the apps it changed. Use it as your daily driver or plug it into your own code-gen pipeline via API.

Full teardown

Amika (YC Fall 2025): teardown vs XMarts

In one line: Amika rents out cloud computers ("devboxes" or "Rigs") where coding agents such as Claude Code and Codex work, for engineering teams, and can run them on the team's own machines for free [site] [docs]. Threat: 2 because it is the same buyer as W1 (small engineering teams running coding agents), live and priced, but it is two people, has no named customers, and sells the place agents run, not trust in the result [site] [yc].

1. Fact file

Item Finding Source
What they say Home page today: "Turn any computer into cloud devboxes for coding agents". Pricing page: "Cloud devboxes for coding agents, on computers you already own". YC line: "Infra to build your own software factory". [site] [yc]
Founded, team, funding YC lists 2023 and a team of 2, Fall 2025 batch, New York. The 2023 date is probably the earlier company, Fixpoint (inference: the pivot is described in the launch post). No funding is stated by them. An aggregator lists a $125k seed with no date or investors, which is UNVERIFIED (it matches the YC standard deal, inference). [yc] [press]
Founders Dylan Mikus (CEO, CMU computer science and machine learning, 2x YC founder) and Jakub Cichon (CTO, 2x YC founder). Both ran Fixpoint first. What YC likely saw: repeat founders who use their own tool for most of their own pull requests (inference, from the launch post claim). YC primary partner: Tom Blomfield. [yc]
Customers None named on the home page, the YC page or the launch post. They claim the founders use Amika for most of their own PRs. [site] [yc]
Price Public. Free: up to 3 active users, unlimited sandboxes on your own machines. Team: $30 a month per active user. Enterprise: custom (SSO, audit logs, "Forward Deployed Engineer"). Hosted compute about $0.37 an hour for a 2-CPU box. No charge for AI tokens (bring your own keys). Job ads: none posted. [site] [jobs]
Path Fixpoint (2023, sourcing and vetting AI trainers) → Amika (Fall 2025, "software factory" with sandboxed agents, five primitives) → persistent "Rigs" and devbox wording (Sep to Oct 2026). The open source repo still sits under the old name gofixpoint. [yc] [press] [docs]
Open source Core CLI, in-VM daemon and TypeScript SDK are Apache-2.0. Control plane and web app are closed. Repo shows 270 stars, 23 forks and 1,399 commits. Ten releases between 30 Sep and 15 Oct. [docs]

2. Their proposition, reverse engineered

Part What they do
Who buys Engineering teams that already run Claude Code or Codex and want agents to work in the cloud, not on one laptop. Head of engineering or founding engineer (inference from the plans and the YC tags).
The pain Code is cheap to make now, but correct code at scale is not. Agents lack a place to test, lack full context, lack hard rules, and teams cannot review the volume (launch post, paraphrased) [yc].
The promise Every agent gets its own cloud computer with the repos, tools and services ready. Work starts from Slack, Linear, the CLI, the web or the API, and a person can take over at any point [site] [yc].
How it works A VM ("Rig") is loaded with repos, secrets and an agent. It can run on the team's own Mac Mini or cloud account, or on Amika's hosted compute. Rigs can be short-lived, long-lived or cloned. Rigs and agents can talk to each other [docs] [press].
The output A running devbox with a private preview link. A pull request with a live preview. The launch post also names rules checked on every change and an audit trail of chats, changes, checks and cost [yc].
Proof style None shown yet. No customers, no numbers. Only "we use it for most of our own PRs" [yc].
Who sells it Self-serve free tier plus "book a demo" [site]. Enterprise plan offers a forward-deployed engineer [site].
Price model Per active user per month, plus per second compute, plus a small fee for extra always-on service sandboxes. Machines you own are never charged [site].
The story Their enemy is clean, throwaway machines: "Forcing cloud agents onto ephemeral VMs is wrong" (CEO, Sep 2026) [press]. Their belief: agents need a persistent, shared workstation that people and agents use together. The page says they are "Not a sandbox provider or agent harness", but a coordination layer [site].

3. Positioning

  • Category they claim: Cloud devboxes for coding agents; earlier, an "operating system" for coding agents and a "software factory" [site] [yc].
  • Category a YC partner would put them in: developer infrastructure for coding agents (sandboxes and environments). Direct rivals in that space sell the same box by the hour (inference; the comparison page was not readable).
  • What they want to be known for: the place where your agents and your team work together, on machines you already own.
  • Where they sit on the map: layers L1/L2/L3 = 1/2/1, buyer = sme, developer.

4. Three layers vs ours

Layer Them (score + evidence) Us (from the system inventory, "Marton's logs show")
L1 Company brain 1. Each Rig gets the repo, config files, MCP servers and a skills library [site] [docs]. Docs describe no memory or learning feature [docs]. A vault of about 1,400 pages, 112 call transcripts and about 8,700 customer quotes, searchable by meaning.
L2 Agent orchestration 2. Several agents at once, agent swarms, Rigs that talk to each other, people take over, access rules and enforced agent configs [site] [docs]. It hosts agents from other makers and does not run its own team design (inference). About 5,600 jobs handed to agents from three makers, each built in its own copy of the code, checked by a different AI, then tests.
L3 Execution and learning 1. The launch post names "automated verification" and rules on every change [yc]. The current site and docs show only CI auto-fix and an audit trail, no measured result feeding the next run [docs] [site]. Scored 1, not 2, because I could not find the checking shipped as a product (inference). About 160 failure records, each with an automatic check. Offer feedback lines fell from 44 to 18 as rules were added. 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 belief Same Coding agents should run in the cloud, often, with people stepping in [yc]. Same: agents code around the clock (brief).
Buyer Same Small engineering teams [site] (inference from plans). W1: small startup teams (brief). No customer yet.
What is sold Different The box agents run in, plus rules and an audit trail [site] [yc]. Agents that do the work and have it checked by a different AI (Marton's logs show).
Who owns the result Different The customer's own agent and harness; Amika says it is not a harness [site]. The system owns the checked result (brief, thesis; unproven on a customer).
How it learns Different No learning loop described [docs]. Rules added from failures and feedback (Marton's logs show, on his own work).
Where it runs Different Your Macs, your cloud, or their hosted compute [site]. Three of Marton's own Macs, wired to his paths. Not sellable yet (system inventory).
Size of team Different Two founders, no jobs posted [yc] [jobs]. Two founders, one of whom does not code (brief).
Proof Different No named customer, no number [site] [yc]. No outside customer; one founder's own logs (brief).
Price Different $30 per user, cheap compute, free on your own hardware [site]. Not set. W1 price idea is value of extra coding hours minus tokens (brief).
Delivery Same Self-serve plus a demo call [site]. Two founders in conversation (brief).

6. Wedge overlap

Wedge Fit Why
W1 Trusted 24/7 coding for small startup teams direct Same buyer and same wish: agents shipping while the team is away. They give the machine and rules; W1 sells the checked result [site] [yc].
W2 Seeing whether your AI agents actually produce adjacent Their audit trail covers sessions, passed checks and cost [yc]. That is a part of W2, but only for agents running inside Amika.
W8 The other 90% of an AI skill adjacent Team plan has a skills library and enforced agent configs [site]. No claim of skill upkeep from real use (UNVERIFIED that none exists).

7. Whitespace (where they stop)

  • Layer gap: they host the agents and name checks and rules, but their public docs describe no learning from checked results [docs]. To own it we need a rule-change log tied to checked runs, with rework falling over several weeks on a real team.
  • Number gap: no named customer and no result, only "we use it ourselves" [yc]. To own it we need one team's workflow with a before/after number (for example pull requests merged a week, or hours until a bug fix).
  • Buyer gap: not true. They already target the small team we want [site].
  • Price gap: not true. $30 a user and free on your own machines is cheap for a small team [site].
  • Speed gap: not true. Free tier and self-serve start in minutes (inference from the plan page) [site].

8. For the YC application

  • Proven today: Marton's logs show his system has run about 5,600 jobs with agents from three makers, each checked by a different AI and then tests, and about 160 failure records each added an automatic check. Amika's public pages show hosting and rules, but no customer and no result [site] [yc].
  • Draft answer to "how are you different from Amika?": DRAFT. "Amika gives your agents a computer. We give you checked work you can trust, and every failure becomes a rule. Our system has run that loop on our own business for five months." Founders say it their own way.
  • Future claim (needs proof): "A small team's agents ship checked code overnight, and the share that needs rework drops each week." Needs one outside team run for 4+ weeks, with a before/after number, and a runner that is not tied to Marton's Macs.
  • What we understand that they don't: the hard part is trusting the output, not the box it runs in, and trust comes from checks that feed back into rules. proven only on Marton's own work (offer feedback lines 44 to 18); needs proof on a customer. Be careful: their launch post already names verification and guardrails [yc].
  • Copyability (M3): medium. They already list verification, guardrails and audit trails as primitives [yc], so a learning loop fits what they say they will build. Against that, their current pages and docs lead with devboxes and say little about checks or learning [site] [docs], the team is two people, and their money comes from compute and seats, not from owning the result (inference). Not hard, so M3 can not score above 3 against Amika alone.
  • Why now (M4): None found in this teardown. Do not use "coding agents are good now": that is general AI progress.
  • Do not claim: that nobody checks agent code (their launch post says they do) [yc]. That we are cheaper or faster to start (they have a free tier). That Amika has no customers (UNVERIFIED: absence of named logos is not absence of users). Any merge rate or reliability claim for our system: only about 15% of jobs reached the main code (system inventory).

9. Ideas worth taking

  1. Run on the buyer's own machines for free and charge for the team layer. It removes the security worry and the cost worry in one move.
  2. Charge per active user, not per seat, so nobody has to ask for a licence to try it.
  3. Ship the core as open source and sell the cloud and control layer. It builds trust with developers fast.

10. Unknowns

  • Whether they have paying customers. Look for case studies on the docs site, their Discord, and the next launch post.
  • What the "vs. Others" comparison page says and which rivals they name. The page text was not readable by fetch; open it in a browser.
  • Real funding. Check the YC page and any seed announcement.
  • Whether "automated verification" is shipped. Read the rest of docs.amika.dev (security, workflows) and try the free tier.
  • Whether they sell in the UK. No UK sign found; check for a Europe cloud region.

Sources

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