AI Coding Tool Bakeoff: A Weighted Scorecard for Tech Leads

You have been handed the job of picking an AI coding tool for your team. Three vendors have demoed. Each demo was impressive in its own way and none of them resembled how your engineers actually work. You have a month to recommend one, and whatever you pick will cost six figures a year and touch every engineer’s workflow.

The right output for this job is not an opinion. It is a scorecard. One that scores the tools against the same tasks, with the same weights, evaluated by multiple engineers from the team that will use it, with a tie-breaker rule defined before any scores come in. That scorecard is this post.

This covers the capability side of evaluation. For the contractual side (training rights, DPA, IP indemnification), see the procurement checklist. The capability scorecard feeds into procurement; no score threshold rescues a tool that fails the procurement gate.

Before You Score

Three setup decisions that must be made before any evaluator touches a tool:

Pick the test codebase. A meaningful bakeoff runs against your code, not synthetic benchmarks. Choose a repository (or a fork) that represents the typical team’s daily work: the language, the framework, the internal conventions, the CI setup. Bakeoffs run on ToDoList demos prove nothing about how the tool will perform on a 200k-line monorepo with custom tooling.

Define the test tasks. Three to five concrete tasks the tool should handle. Not “write a function that does X” — something more like “add a new endpoint that follows our existing /api/* route conventions, with our auth middleware, our input validation library, and matching tests.” These tasks are the same across tools. Vendors cannot cherry-pick.

Assign 3–4 evaluators. Include one evaluator from each major role the tool will affect: backend, frontend, platform/infra. Evaluators score independently; aggregation happens at the end.

The Scorecard

Ten criteria grouped into four categories. Each criterion has a weight (summing to 100), scored 1–5 by each evaluator. The tool’s score is the weighted average across evaluators. Criteria marked [gate] are disqualifying if scored ≤2 by any evaluator.

Capability (50%)

#	Criterion	Weight	Scoring guidance
C1	Quality of generated code on the test tasks [gate]	15	5 = ships with minor edits, 3 = significant review needed, 1 = throwaway
C2	Adherence to codebase conventions	10	How well does it pick up your existing patterns from context?
C3	Refactoring multi-file changes	10	Can it edit 3+ files coherently, or does it propose 3 disconnected edits?
C4	Debugging assistance	8	Given a failing test, can it diagnose and propose a fix that actually fixes?
C5	Test generation	7	Are generated tests meaningful or assertion-free placeholder shells?

Workflow fit (25%)

#	Criterion	Weight	Scoring guidance
W1	IDE integration quality	10	Smoothness in the editor(s) your team actually uses — not a demo VS Code
W2	CLI / terminal integration	8	Can engineers who live in the terminal use it without switching?
W3	Latency on your typical prompt size	7	P50 response time under realistic context load

Admin and visibility (15%)

#	Criterion	Weight	Scoring guidance
A1	SSO + provisioning [gate]	5	Works with your identity provider out of the box
A2	Usage analytics (per-user token/cost)	5	Can you see who is using it how? Can you set quotas?
A3	Observability of prompts and outputs for audit	5	Configurable retention, export, compliance with your governance policy

Team experience (10%)

#	Criterion	Weight	Scoring guidance
T1	Onboarding time for a new engineer	5	How long until a new hire is effective?
T2	Documentation and learning curve	5	Is the vendor docs good enough that your team leads can self-serve?

Total weight: 100. Tools are scored per evaluator, then averaged. A tool that scores ≤2 on any [gate] criterion from any evaluator is out, regardless of total.

How to Run the Bakeoff

1. Set up all tools in parallel. Each tool gets the same test codebase, same auth setup, same evaluator accounts. A 2-week minimum trial window — anything shorter and evaluators haven’t built intuition.
2. Each evaluator does the test tasks with each tool. Independently. No scoring discussion until all evaluators have finished.
3. Score independently. Give evaluators the scorecard template, but do not let them see each other’s scores. Convergence-to-first-opinion is the single largest source of bakeoff bias.
4. Aggregate. Average the scores per criterion across evaluators. Total weighted score per tool. Flag any criteria with >1.5 standard deviation across evaluators for discussion.
5. Discuss the divergences, not the totals. The informative conversation is “why did backend-evaluator rate C3 as 4 while platform-evaluator rated it as 2?” That disagreement is usually either a misunderstanding of the criterion (fixable) or a real difference in how the tool handles one team’s workflow versus another’s (important to surface).

The Tie-Breaker Rule

Total scores within 5 points of each other are a tie for practical purposes. Pre-declaring the tie-breaker before the numbers are in prevents the rationalization that happens after. A workable rule of thumb:

1. Procurement viability first (see the procurement checklist). A tied tool that fails a contract clause is out regardless.
2. Trajectory of improvement next. Which vendor has shipped the most meaningful releases in the last six months? Which has the more credible roadmap? A tool that’s 2nd today but moving fastest beats a tool that’s 1st and stagnant.
3. Developer preference last. When the top two are indistinguishable on every other axis, go with the one the evaluators actually preferred to use. The preference signal is noisy, but it becomes load-bearing at the tie.

Declaring these priorities in advance takes an hour. Re-litigating them when the scores come in close can derail a quarter.

Anti-Patterns

Vendor-led POC. Letting the vendor configure, deploy, and run the POC produces a curated demo dressed up as a trial. Insist on your team driving; the vendor is on-call for support.

Scoring on subjective headline quality. “The output feels better” is a valid observation but not a score. Anchor scores to the criterion language and the numeric rubric. If it’s not in the rubric, it doesn’t count.

Running the bakeoff only with power users. Your most enthusiastic AI users will score every tool above baseline. Include at least one evaluator who is skeptical or neutral — they catch failure modes the enthusiasts rationalize.

Ignoring price until the end. Price does not appear in the scorecard because it is a budget decision, not a capability decision. That said, if two tools score within the tie zone and one is 3× the price, run the full ROI calculation before the final decision.

Re-running the bakeoff to validate a preferred tool. If the bakeoff you ran produced a result you don’t like, the temptation is to tweak the weights until your preferred tool wins. The weights must be set before the scoring. Post-hoc weight adjustment invalidates the whole exercise.

What the Scorecard Isn’t

This scorecard evaluates tools against tasks. It does not evaluate:

• Whether AI coding tools are worth adopting in the first place — that’s a strategic question, see executive buy-in.
• How to roll the tool out once selected — see the pilot program guide and the team rollout post.
• Which tools currently lead the market — that’s a comparison table, see best AI toolsets for dev teams. That post ranks; this post helps you rank them for your context.

Handoffs

• To procurement (procurement checklist) — the scorecard output is a ranked capability list. Procurement applies its contract-term checklist to the top candidates. Both must pass; either can veto.
• To leadership (executive buy-in) — the scorecard is the evidence artifact that goes into the one-page business case. “We evaluated three tools on 10 criteria with 4 evaluators” beats “we picked the one we liked” every time.

The bakeoff takes roughly a month done properly. That is cheap insurance on a contract that will run for a year or more.