Navigara Launches ’The 500 OSS Performance Index’: A Live Benchmark of Engineering Output Across OpenAI, MSFT, GOOG, and Meta
Built as a deterministic standard to verify AI productivity claims, the index reveals a 6x spread in engineering output across major tech giants

"The market is full of productivity claims built on controlled trials that do not resemble production conditions," said Jirka Bachel, Founder and CEO of Navigara. "The 500 OSS Index measures what actually merged, scored the same way for every org, with a methodology available for anyone to inspect. That is the standard engineering leaders need right now, and it is the one we intend to hold ourselves to as well."
AI vendors are selling productivity, but most of the evidence comes from their own controlled trials, surveys, or opaque benchmarks. Engineering leaders are currently making massive budget decisions based on numbers they cannot independently verify, against baselines they do not have, using methodologies they have never seen. Today, Navigara launches The 500 OSS Performance Index: a live, public benchmark tracking the actual engineering output of Microsoft, Meta, OpenAI, Vercel, Google, and Cloudflare. Scored via a deterministic measurement applied to every merged commit and calibrated entirely in the open, the index provides the baseline the industry has been missing.
The Core Data: A 6x Performance Spread
While average engineering output across the six cohort organizations rose 124.8% over the trailing 90-day rolling series (from 0.86 to 1.94 ETV per developer per month), performance is radically non-uniform. The index reveals a massive gap between the highest and lowest performing engineering orgs.
How ETV Measures True Output (Not Just Lines of Code)
The 500 OSS Performance Index completely bypasses easily gamed metrics like lines of code or commit counts. Instead, it utilizes Engineering Throughput Value (ETV), which scores every merged file change by the depth of work it represents:
- Structural Weight: The complexity of the change itself
- Surface Area: The context a developer had to understand to land it safely
- Feature Graph Position: Where the code sits within the broader architecture
- Defect Correction: Whether it fixes a bug introduced by someone else
The Three-Bucket Architecture
To prevent data manipulation, output is reported in three strict, non-additive buckets that never collapse into a single deceptive score:
- Growth: Net-new capability (increased its share by 4.4 percentage points over the last 90 days)
- Maintenance: Sustaining work (decreased by 7.1 points)
- Fixes: Rework and repairs
The scoring engine is deterministic: the same diff in the same context produces the same score. The full methodology is available for inspection at 500.navigara.com/methodology.
Introducing the AI Spend Calculator (Beta)
What does an AI budget actually buy? To help engineering leaders answer the inevitable questions from their CFO, the index includes a public AI Spend Calculator. The calculator allocates a hypothetical AI budget across Growth, Maintenance, and Fixes based on each organization’s actual work mix and reports the true cost per ETV delivered. It is designed to give leaders a repeatable framework for determining exactly where AI investments sit in their codebase.
Calibrated in the Open
“The market is full of productivity claims built on controlled trials that do not resemble production conditions,” said Jirka Bachel, Founder and CEO of Navigara. “The 500 OSS Index measures what actually merged, scored the same way for every org, with a methodology available for anyone to inspect. That is the standard engineering leaders need right now, and it is the one we intend to hold ourselves to as well.”
Navigara openly acknowledges a commercial interest in proving that current engineering measurement is insufficient. To maintain absolute integrity, every number in the index is traceable to a documented, identical formula. Outside organizations can benchmark their own teams against the index, publicly or privately, at 500.navigara.com/benchmark.
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