Hot Take AI coding tools are not shrinking labor, they are inflating expectations and quietly extending the workday, a classic setup for EBITDA erosion.
Productivity Optics vs Labor Reality
The narrative sold to investors is clean, fewer engineers, faster output, expanding margins. The operational data is messier. Developers using AI are shipping more code, but they are also reviewing more output, debugging generated artifacts, and managing edge cases the models cannot reliably solve. The result is not labor substitution, it is labor amplification. Hours expand to match inflated throughput expectations. Management interprets higher output as latent capacity, not as incremental strain.
This creates a valuation trap. Public market comp sheets reward perceived efficiency gains, yet the cost base does not compress. Instead, compensation stays sticky while utilization rises. Burn looks stable, but human capital fatigue accumulates off balance sheet until attrition forces a reset.
Cap Table Pressure Builds
Longer hours without proportional compensation improvement trigger retention risk. Top engineers, already scarce, interpret AI tooling not as leverage but as surveillance and quota expansion. That translates into higher cash demands and larger equity refresh grants. The cap table absorbs the damage. What looked like a tool driven margin expansion story mutates into a cap table bloodbath as companies pay to retain talent operating at unsustainable intensity.
Private companies are especially exposed. Their valuation narratives rely on future margin expansion via automation. If AI does not reduce headcount, but instead raises performance expectations, the projected margin curve flattens. Down rounds follow when growth decelerates and cost discipline proves illusory.
M and A Repricing Risk
Strategic buyers and private equity have been underwriting deals on the assumption that AI will compress engineering spend post acquisition. That assumption weakens as real world usage shows longer developer hours and persistent complexity overhead. Diligence teams will start adjusting quality of earnings, discounting projected cost savings tied to AI adoption.
Multiples will follow. Software assets marketed as AI leveraged efficiency plays risk multiple compression when buyers recognize the mismatch between output and actual labor reduction. What commands a premium today could trade at a discount once EBITDA erosion appears in audited numbers.
Management Incentives Misaligned
Leadership teams are incentivized to showcase rapid AI adoption, not to surface hidden labor expansion. Internal reporting emphasizes velocity metrics, commits, features shipped, while ignoring human cost. This misalignment delays corrective action. By the time fatigue and attrition show up in financials, the organization has already normalized overextension.
The end state is predictable. Either firms recalibrate expectations and accept slower output, or they continue extracting more hours until the workforce forces a repricing through turnover. In both scenarios, the clean AI margin expansion story breaks, and investors reassess the entire sector with sharper skepticism.