Atlas is a terminal-native AI coding agent that pairs with Haskell so it reasons about your type signatures, typeclass instances, and Cabal targets instead of guessing at them. In 2026 you run atlas in a project with a .cabal file or a stack.yaml, and Atlas iterates on the diff against GHC type errors until it typechecks.
Why Haskell developers use Atlas
Haskell developers use Atlas in 2026 because a type signature is the specification. Atlas reasons about your type signatures, typeclass instances, and Cabal targets instead of guessing at them, so a change is shaped by types that exist rather than a plausible pattern.
Haskell punishes the failure mode most AI coding tools have, which is producing code that merely looks right. A wrong instance, a missing constraint, or a partial pattern match does not slide past review, it stops the build outright. That makes Haskell an unusually good fit for an agent grounded in real declarations. Atlas indexes code by AST declarations using tree-sitter, so a type signature, an instance head, or a data declaration is retrieved intact. A signature severed from its definition by a line window is worse than useless here, because in Haskell the signature is the part carrying the meaning and the definition is close to a footnote.
Starting Atlas in a Cabal or Stack project
Setup in 2026 takes one command: run atlas in a project with a .cabal file or a stack.yaml. Atlas then reads your module hierarchy, language extensions in default-extensions, and build-depends bounds, which keeps a suggestion inside the dialect your project actually enables.
Language extensions are the hidden dialect problem in Haskell. Code that compiles happily in a project with GADTs and TypeFamilies enabled will not compile in one without them, and an agent that never read the default-extensions field produces exactly that mismatch and then blames the compiler. Build-depends bounds are the same story a level up: a function that exists in a newer version of a library but not the one your bounds permit is a suggestion that wastes a compile cycle. Reading the module hierarchy, the extensions, and the bounds is how Atlas writes to your project rather than to Haskell in the abstract.
Eliminating partial functions and adding hspec suites
The daily Haskell loop in 2026 is precise: ask Atlas to eliminate a partial function or add an hspec suite to the test-suite stanza. Replacing head with a total alternative changes a return type, which breaks every call site that assumed the old one.
Threading a Maybe or an Either through the chain until the whole thing typechecks again is exactly the sort of wide, mechanical, compiler-guided work worth delegating. GHC will find every one of those call sites, but somebody still has to fix them, and that somebody does not need to be you. Adding an hspec suite to the test-suite stanza means editing the .cabal file as well as writing the specs, because a test module that is not listed under other-modules simply will not be built, which is a confusing failure the first time you meet it.
Letting cabal build and GHC type errors drive the loop
Atlas can run cabal build to surface GHC type errors, then iterate on the diff until it typechecks. In 2026 that turns the GHC type checker into the agent's feedback signal, a far stronger correctness gate than a dynamic language can offer.
The compiler is a reviewer that never gets tired, and GHC is the strictest one in common use. Because Atlas can run cabal build and iterate against the type errors, a refactor arrives as a change that already compiles rather than a hopeful suggestion you get to debug on its behalf. Every Atlas tool call is permission-gated against allow, ask, and deny rules, so invoking cabal build is a permission you grant deliberately. Atlas can also apply fourmolu to the changed modules before you approve the commit, keeping the diff about types rather than layout.
Review and rollback when typechecking is not enough
Atlas computes a unified diff for every file edit and surfaces it for approval before writing, and it snapshots file changes as git patches, which is the rollback path a Haskell refactor needs in 2026. Code that typechecks can still be wrong, and that is the part newcomers underestimate.
A totality refactor that compiles can still change strictness, alter evaluation order, or turn a modest fold into a space leak that eats memory until the process dies, and GHC will not object to any of it. Laziness means the gap between correct types and correct behavior is real and occasionally expensive. So the human gate stays: Atlas drafts a plan in a read-only plan agent and asks before switching to a build agent, giving you the module list before the first edit, and the commit waits until cabal build is clean and hspec passes.
Getting started
- 01Run atlas in a project with a .cabal file or a stack.yaml.
- 02Let Atlas read your module hierarchy, language extensions in default-extensions, and build-depends bounds.
- 03Ask Atlas to eliminate a partial function or add an hspec suite to the test-suite stanza.
- 04Have Atlas run cabal build to surface GHC type errors, then let it iterate on the diff until it typechecks.
- 05Let Atlas apply fourmolu to the changed modules before you approve the commit.
- 06Check the diff for strictness changes, since a refactor can typecheck and still leak space.
Frequently asked questions
- can an AI agent write Haskell that actually typechecks
- Atlas can run cabal build to surface GHC type errors, then iterate on the diff until it typechecks, so the change you review already compiles rather than merely looking correct.
- does Atlas understand language extensions in a Haskell project
- Yes. Atlas reads your module hierarchy, language extensions in default-extensions, and build-depends bounds, so it writes to your project's dialect rather than to Haskell in the abstract.
- can Atlas remove partial functions from Haskell code
- Yes. Ask Atlas to eliminate a partial function or add an hspec suite to the test-suite stanza. Replacing head means threading a Maybe through every call site until the chain typechecks.
- does Atlas work with Cabal and Stack
- Yes. Run atlas in a project with a .cabal file or a stack.yaml. Atlas reasons about your type signatures, typeclass instances, and Cabal targets instead of guessing at them.
- will an AI agent reformat my Haskell modules
- Atlas can apply fourmolu to the changed modules before you approve the commit, so the diff stays about types and behavior rather than formatting.
- how do I stop an AI agent from running cabal build without asking
- Every Atlas tool call is permission-gated against allow, ask, and deny rules, so cabal build executes only when you allow it.
- if Haskell code typechecks is an AI refactor safe
- Not necessarily. A refactor can typecheck and still change strictness or introduce a space leak, so Atlas snapshots file changes as git patches and you review the diff before it is written.
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