Agentic coding has the promise to unlock a turbocharged workweek, cranking out pull requests faster than any keyboard warrior could manually manage. The real bottleneck isn’t how quickly code appears—it's how quickly humans can keep up with the reviews. If you’re thinking about coasting on those newly liberated hours, beware: the pace is relentless and those who snooze will get lapped. Adapt, hustle, and wield your extra time, or get comfortable watching the leaderboard from the bottom.
PS! I continue to recommend human code reviews and remain open to updating my perspectives as AI evolves :)
Short take: review is the constraint; ship more anyway.
A PR takes ~6 hours to write and 15–20 minutes to review—per reviewer. Agentic coding (Copilot and friends) doesn’t cancel your review policy; it makes it matter. As adoption spreads, you spend more time reviewing and still ship more.
It does not matter if the agentic multiplier is 1.2x, 2x, 4x or more, your team will still benefit. However, when does that flip and review starts choking the flow? Read on.
It doesn’t “flip” mathematically, but in practice review starts choking the flow when mr ≈ 1 — about 10× coding speed with two reviewers (r≈0.097) or ~20× with one (r≈0.049) given 6h/PR and 15–20m per reviewer.
Assumptions (and please argue my assumption data)
- One author. We model one‑reviewer and two‑reviewer policies.
- Coding per PR ≈ 6h. Review per reviewer ≈ 15–20m. (Yes, short. Keep it that way.)
- That gives a review/coding ratio r per reviewer of ~0.042–0.056; we use ~0.049. Two reviewers ≈ double r.
- Agentic coding is a multiplier m on coding speed (1.2×, 1.5×, 2×, 3×, 4×).
Light math, heavy impact
Split the week between writing and reviewing. If writing gets m× faster, more PRs arrive, so review minutes go up. A back‑of‑napkin math formula for team throughput vs. today:
gain ≈ m·(1+r) / (1+m·r)
r is total human review time divided by authoring time for a PR. Bigger r → more RAT (Review-Added Tapering): the gains flatten as review effort eats into coding speedups.
Case A — One human reviewer
Throughput climbs, and review time takes a bigger slice of the week, but you have headroom at these review times.
Figure 1 — Team throughput vs. agentic multiplier (one reviewer; 15–20 min sensitivity band).
Figure 2 — Share of team time spent on review (one reviewer).
Case B — Two human reviewers
Two required approvals roughly double review time per PR, so you feel the constraint sooner. 
Figure 3 — Team throughput vs. agentic multiplier (two reviewers; sensitivity band).
Figure 4 — Share of team time spent on review (two reviewers).
Clearer throughput tables
Two quick tables; both assume a team of eight and the same PR size/quality.
Table A — Adoption curve (8 people; each adopter is 1.2×)
| Adopters (of 8) | Avg multiplier (m̄) | Throughput × (1 reviewer) | Throughput × (2 reviewers) |
|---|---|---|---|
| 0 | 1.000 | 1.00 | 1.00 |
| 1 | 1.025 | 1.02 | 1.02 |
| 2 | 1.050 | 1.05 | 1.05 |
| 3 | 1.075 | 1.07 | 1.07 |
| 4 | 1.100 | 1.09 | 1.09 |
| 5 | 1.125 | 1.12 | 1.11 |
| 6 | 1.150 | 1.14 | 1.13 |
| 7 | 1.175 | 1.17 | 1.16 |
| 8 | 1.200 | 1.19 | 1.18 |
Table B — Throughput as average team multiplier grows (to 4×)
| Avg multiplier (m̄) | Throughput × (1 reviewer) | Throughput × (2 reviewers) |
|---|---|---|
| 1.0× | 1.00× | 1.00× |
| 1.2× | 1.19× | 1.18× |
| 1.5× | 1.47× | 1.44× |
| 2.0× | 1.91× | 1.84× |
| 3.0× | 2.75× | 2.55× |
| 4.0× | 3.51× | 3.16× |
About those “free” minutes
Agentic coding frees time. If it doesn’t become more (or better) PRs, it still has to land somewhere:
- Best: quality. More tests, tighter diffs, cleaner commits. Review gets faster when diffs are tidy.
- Good: non-code work. Specs, comms, reviews, mentoring—all the glue.
- Worst: Xbox/Netflix. Teams that reward shipped work will see the reinvestors lap the coasters.
Push the pivot out
- Keep PRs small—cheap to read is cheap to ship.
- Let CI and AI do pre-review: lint/tests/security, AI summaries and risk flags.
- Block time for review—don’t background it.
- Two approvals only when it truly buys risk down.
Bottom line
Manual review doesn’t kill agentic gains. With 6h write / 15–20m per reviewer, one-approval teams have plenty of headroom; two-approval teams still gain but meet the review wall sooner. Convert freed minutes into smaller, better PRs—or more of them— and the meter on shipped work keeps spinning faster.
