Update ROADMAP.md

ROADMAP.md

@@ -7,40 +7,39 @@ There are three main milestones we believe will greatly increase gpt-engineer's
 
 ## Our current focus:
 
-- [x] Continuous evaluation of our progress 🎉
+- [x] **Continuous evaluation of our progress 🎉**
   - [x] Create a step that asks “did it run/work/perfect” in the end of each run [#240](https://github.com/AntonOsika/gpt-engineer/issues/240) 🎉
   - [x] Collect a dataset for gpt engineer to learn from, by storing code generation runs 🎉
   - [ ] Run the benchmark multiple times, and document the results for the different "step configs" [#239](https://github.com/AntonOsika/gpt-engineer/issues/239)
   - [ ] Document the best performing configs
-- [ ] Self healing code
+- [ ] **Self healing code**
   - [ ] Run the generated tests
   - [ ] Feed the results of failing tests back into LLM and ask it to fix the code
-- [ ] Let human give feedback
+- [ ] **Let human give feedback**
   - [ ] Ask human for what is not working as expected in a loop, and feed it into GPT4 to fix the code, until the human is happy
-- [ ] Improve existing projects
+- [ ] **Improve existing projects**
   - [ ] Decide on the "flow" for the CLI commands and where the project files are created
   - [ ] Add an "improve code" command
   - [ ] Design how gpt-engineer becomes a platform
   - [ ] Integrate Aider
 
 ## Experimental research
-This is not current focus, but if you are interested in experimenting, please
-create a thread in our discord share your intentions in Discord's #general, and your findings as you
-go along.
-- [ ] Make code generation become small, verifiable steps
+This is not our current focus, but if you are interested in experimenting: Please
+create a thread in Discord #general and share your intentions and your findings as you
+go along. High impact examples:
+- [ ] **Make code generation become small, verifiable steps**
   - [ ] Ask GPT4 to decide how to sequence the entire generation, and do one
   prompt for each subcomponent
   - [ ] For each small part, generate tests for that subpart, and do the loop of running the tests for each part, feeding
 results into GPT4, and let it edit the code until they pass
-- [ ] Ad hoc experiments
+- [ ] **Ad hoc experiments**
   - [ ] Try Microsoft guidance, and benchmark if this helps improve performance
   - [ ] Dynamic planning: Let gpt-engineer plan which "steps" to carry out itself, depending on the
 task, by giving it few shot example of what are usually "the right-sized steps" to carry
 out for such projects
 
 ## Codebase improvements
-By improving the codebase and developer ergonomics we accelerate development
-acroess the board. A lot can be done, here are some examples:
+By improving the codebase and developer ergonomics, we accelerate progress. Some examples:
 - [ ] Set up automatic PR review for all PRs with e.g. Codium pr-agent
 - [ ] LLM tests in CI: Run super small tests with GPT3.5 in CI, that check that simple code generation still works