The hottest Metrics Substack posts right now

And their main takeaways
Category
Top Technology Topics

My Fitbit Buzzed and I Understood Enshittification

Software Design: Tidy First? • 3910 implied HN points • 14 Jan 26
🕹 Technology Metrics
  1. Relying on metrics to prove value pushes teams to optimize numbers instead of actual user delight, which leads to annoying features like unsolicited notifications or easy-to-hit call buttons.
  2. Adding more metrics creates an arms race where people game the measurements and complexity grows until nobody knows what 'good' really means, so metrics end up replacing real product quality.
  3. A better approach is to adopt simple principles—like don't interrupt users or put buttons where they'll be pressed by accident—and defend those rules even when they aren't measurable on a dashboard.

TBM 408: Basic Links

The Beautiful Mess • 714 implied HN points • 25 Feb 26
💼 Business Metrics
  1. Shipping creates the potential for outcomes rather than delivering final results, and each change starts a chain of hypotheses and assumptions you must test. Uncertainty in those links is normal and points to where you need to learn or take a leap.
  2. Changes usually set off multiple impact paths that affect different users, metrics, and timeframes. Start with clear, actionable inputs, name the immediate effects you expect, and connect those to longer-term outcomes.
  3. Strategy and research help you choose where to act, form causal hypotheses, and decide what signals to measure instead of only chasing lagging metrics. Build a roadmap of researched options, set goals for actions or early signals as well as long-term results, and iterate.

The Analytical Skills No One Teaches You

SeattleDataGuy’s Newsletter • 1165 implied HN points • 23 Jan 26
💼 Business Metrics
  1. Practice analytical intuition by doing rough estimates, breaking problems into proxy values, understanding baselines and natural variance, and always running manual spot checks instead of blindly trusting tooling.
  2. When a metric moves unexpectedly, first confirm the data with multiple sources, then generate and test product, market, user, and external hypotheses to pinpoint the root cause and escalate with concrete analysis.
  3. Choose KPIs that are relevant, measurable, specific, prioritized, and balanced — pick the right type (North Star, top-level, secondary, or OMTM), avoid vanity metrics, and use simple, trusted proxy metrics tailored to your product.

TBM 403: The Seduction (And Folly) Of Rollups, Points, and (Most) Time Tracking

The Beautiful Mess • 542 implied HN points • 27 Jan 26
💼 Business Metrics
  1. Rollups, story points, and detailed time tracking feel like neat accounting but are really proxies and guesses, and over-relying on them leads teams to game metrics or manage the proxy instead of the real work.
  2. Time allocation is not the same as capacity — capacity is emergent and built over time — so measurement approaches must match the nature of the system rather than forcing every team into a single rollup model.
  3. Focus on outcome-oriented, low-cost signals that support decisions (like releases, customer impact, dependencies, and flow metrics), connect work to goals when it makes sense, and use rough estimates instead of chasing false precision.

TBM 402: The Real-World Journey to Value and Product-Centricity

The Beautiful Mess • 595 implied HN points • 19 Jan 26
🕹 Technology Metrics
  1. Change typically begins with a focus on delivery predictability and reducing work-in-progress, where throughput is treated as the main measure of value.
  2. Introducing goals or OKRs shifts attention toward outcomes, but real outcome orientation only sticks when teams, architecture, funding, and ways of working are redesigned so objectives guide work as testable hypotheses.
  3. The healthiest state is when value models underpin org design, goals, funding, and architecture so technology is inseparable from the business, but there is no final destination—models keep evolving and organizations can regress.
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UX Roundup: GUI Heroes | Great AI Videos | AI Won’t Kill Software | Bing GEO | AI Capability Growth | Google AI UX | One-Shot Video | GPT 5.4 Writing

Jakob Nielsen on UX • 29 implied HN points • 09 Mar 26
🕹 Technology Metrics
  1. AI is improving fast across images, video, and language. New models make much better visuals and one-shot instructional videos, GPT 5.4 writes more compellingly, and capability metrics show AI handling longer expert tasks.
  2. AI won’t kill software — it will make building software cheaper and open much larger markets, though legacy vendors that don’t adapt may be disrupted while AI-native firms and new business models grow.
  3. Website visibility now requires Generative Engine Optimization (GEO) instead of just SEO; tools like Bing’s AI Performance help measure AI citations, which are often highly concentrated, so focus on your top pages and track the AI grounding queries that drive citations.

How Tech Metrics Change Your Values and Behaviour

SatPost by Trung Phan • 223 implied HN points • 24 Jan 26
🕹 Technology Metrics
  1. External metrics like scores, ratings, and likes can come to define your values and make you chase numbers instead of what truly matters to you.
  2. Metrics are not neutral: they embed the priorities of their designers and tend to flatten rich, qualitative experiences into simple numbers that reward shallow, attention-grabbing behaviour.
  3. You can resist value capture by being intentional—pair or balance indicators, trust anecdotes when metrics feel wrong, limit exposure to harmful scores, and treat platform scoring systems like optional games you can enter or leave.

The Link in Bio Guide to Goal Setting

Link in Bio • 904 implied HN points • 25 Jan 24
💼 Business Metrics
  1. Understand the difference between goals and intentions in social media strategy.
  2. Set SMART goals - Specific, Measurable, Achievable, Relevant, Timely - for success.
  3. Track, adjust, and report on goals regularly to drive social media progress.

Developer Productivity Metrics: Education Necessary

Software Design: Tidy First? • 2098 implied HN points • 29 Jan 25
🕹 Technology Metrics
  1. Metrics can help improve productivity, but they can also be misunderstood or misused. It's important to communicate them clearly and use them to support developers instead of pressure them.
  2. Goodhart's Law reminds us that when a measure becomes a target, it can lose its value. This means we need to be careful about how we use metrics to avoid gaming the system.
  3. It's crucial to focus on improving the developer experience, not just making them happy. Measuring effectiveness can help identify and eliminate roadblocks that slow down productivity.

Palantir (PLTR) Q4 Earnings Review

Stock Market Nerd • 687 implied HN points • 06 Feb 24
💰 Finance Metrics
  1. Palantir beat revenue and profit estimates, showing strong demand and profitability growth.
  2. Balance sheet details indicate a healthy financial position with no traditional debt and significant cash reserves.
  3. The company has shown impressive growth, particularly in the U.S. commercial sector, and is poised for further success with its AI platform.

Metrics Are The Map, Not The Territory

Push to Prod • 59 implied HN points • 30 Jul 24
🕹 Technology Metrics
  1. Metrics give us a view of our systems, but they won't show the complete picture. It's like looking at a map; it can guide us but doesn't capture all the details.
  2. When we check the data, we might miss important moments because of how we sample information. This can lead to misunderstandings about our system's performance.
  3. Understanding that metrics are imperfect helps us make better decisions. We should use them to create theories, not think they tell us everything.

Cost of Acquisition (CAC) trap.

Elena's Growth Scoop • 1022 implied HN points • 12 May 23
💼 Business Metrics
  1. Focus on optimizing payback period instead of just reducing CAC to improve ROI.
  2. Consider the profitability and long-term value of different acquisition channels before shutting them down based solely on CAC.
  3. The payback period is a superior metric for acquisition that focuses on reinvesting returns and optimizing various aspects like CAC, conversion rate, ARPU, and conversion time.

GraphRAG Analysis, Part 1: How Indexing Elevates Knowledge Graph Performance in RAG

AI Encoder: Parsing Signal from Hype • 70 HN points • 09 Jul 24
🕹 Technology Metrics
  1. Knowledge graphs do not significantly impact context retrieval in RAG, as all methods showed similar context relevancy scores.
  2. Neo4j with its own index improved answer relevancy and faithfulness compared to Neo4j without indexing and FAISS, showcasing the importance of effective indexing for precise content retrieval in RAG applications.
  3. Developers need to consider the trade-offs between ROI constraints and performance improvements when deciding to use GraphRAG, especially in high-precision applications that require accurate answers.

All you need is Wide Events, not “Metrics, Logs and Traces”

A Song Of Bugs And Patches • 224 HN points • 15 Feb 24
🕹 Technology Metrics
  1. The concept of 'Wide Events' is proposed as a simpler and more effective approach to observability than the traditional 'Metrics, Logs, and Traces'.
  2. Older systems like Open Telemetry may contribute to confusion by categorizing data into distinct pillars, making observability seem complex.
  3. A system like Scuba, based on 'Wide Events', enables streamlined investigation and data exploration, emphasizing the importance of simplicity in observability tools.

How To Measure Data Quality - Issue 185

Data Analysis Journal • 235 implied HN points • 07 Feb 24
🕹 Technology Metrics
  1. Data quality metrics are essential for measuring data governance and analytics success.
  2. There is no industry standard for defining poor-quality data; it varies based on context.
  3. Having specific KPIs for data quality is crucial to scale data governance initiatives and improve the state of data quality.

Improving Retention with Audience Surveys

Growth Croissant • 452 implied HN points • 12 May 23
💼 Business Metrics
  1. Improving retention by solving the customer's problem in a deeper way can have a noticeable impact on retention.
  2. Focus on your core audience for a 10x improvement in solving their problem, even if it means neglecting parts of your audience for better problem-solving.
  3. Running surveys, especially cancel surveys, can provide valuable feedback to enhance your product, understand audience needs, and improve retention.

Is EBITDA Really Bullshit? Answer: "It Depends"

Value Investing Substack • 353 implied HN points • 05 Aug 23
💰 Finance Metrics
  1. EBITDA can be a controversial metric in finance, with some calling it 'bullshit earnings'.
  2. John Malone successfully used EBITDA to communicate TCI's growth strategy in cable industry.
  3. Valeant Pharmaceuticals' misuse of EBITDA led to financial trouble, highlighting the importance of understanding the context behind EBITDA figures.

No more coding vibes in the efficiency era

Dev Interrupted • 210 implied HN points • 19 Jun 25
🕹 Technology Metrics
  1. The focus on just hiring more engineers is outdated. Now, it's important to measure productivity based on real outcomes and impact rather than just feelings.
  2. AI can help with tasks, but it doesn't understand your specific business context. It's important to use AI wisely and not rely on it for critical thinking or decision-making.
  3. To improve productivity, teams need clear context and communication about goals. Understanding the 'why' behind their work is essential for success.

Your guide to the 2024 SaaS benchmarks

Kyle Poyar’s Growth Unhinged • 504 implied HN points • 21 Nov 24
💼 Business Metrics
  1. 2024 sees stabilization in SaaS growth rates, with early stages performing better while larger companies struggle. Smaller startups are showing stronger growth despite an overall slowdown.
  2. Early stage SaaS and AI companies are thriving, significantly increasing growth rates and maintaining lean teams. They are using automation and smart hiring to succeed.
  3. There's a shift in pricing models for AI products, with many still using traditional subscription models but a growing number exploring usage-based and outcome-based pricing. It's a sign of changing market demands.

Thoughts on SentinelOne

Hard Mode by Breaking SaaS • 275 implied HN points • 03 Jun 23
💼 Business Metrics
  1. Reporting accurate ARR metrics is crucial for SaaS companies' credibility.
  2. Having a proper forecasting methodology and CRM setup is essential for financial success.
  3. Investor confidence in a company can be greatly impacted by unexpected changes in reported metrics.

Why Data Teams Need to Understand Metrics: A Look at Starbucks’ Comparable Store Sales

SeattleDataGuy’s Newsletter • 447 implied HN points • 08 Nov 24
💼 Business Metrics
  1. Data teams need to know the main numbers that matter for their business. This helps them understand how the company is performing.
  2. High-level metrics like revenue and expenses can seem too big to grasp. Breaking these down into smaller parts makes them easier to understand.
  3. These smaller, detailed metrics can reveal valuable insights that affect decisions and strategies for the business.

Lifetime Value for Crypto Businesses

DeFi Weekly • 255 implied HN points • 03 Apr 23
🔮 Crypto Metrics
  1. Understanding the concept of Lifetime Value (LTV) is crucial for crypto businesses as it determines how much a customer is worth in terms of fees earned over their lifetime.
  2. For different categories like chains, DEXs, lending, stablecoins, and yield aggregators, there are specific frameworks to optimize customer lifetime value based on factors like transaction size, fees applied, profit earned, and performance fees.
  3. Each crypto primitive operates similar to traditional businesses but with unique mechanics due to the nature of the crypto environment, such as the impact of costs on profits and the challenge of optimizing incentive elasticity.

☁ God Bless Klaviyo

Hard Mode by Breaking SaaS • 235 implied HN points • 01 Sep 23
💼 Business Metrics
  1. Klaviyo's efficiency is part of their success with a high CAC Payback and low burn rate.
  2. Klaviyo's strong NRR of 119% is driven by price increases, customer contact growth, and new product launches.
  3. Klaviyo, as a purpose-built SaaS platform, combines data analytics and marketing to offer a unique solution.

Unintended Consequences

Fish Food for Thought • 20 implied HN points • 17 Dec 25
🕹 Technology Metrics
  1. Unintended consequences are inevitable; well-meaning fixes can create worse problems or surprising new opportunities, so assume surprises will happen.
  2. Chasing metrics without context makes products drift from their purpose, because optimizing numbers can reward harmful or shallow behaviors; always measure real human outcomes and watch for distortions.
  3. Treat every launch as the start of learning: test for misuse, listen to real users, and build a culture that adapts quickly instead of blaming mistakes.

The Measurement Problem in Software Engineering

Maestro's Musings • 17 implied HN points • 15 Dec 25
🕹 Technology Metrics
  1. Counting artifacts like lines of code, story points, or PR counts has repeatedly failed; these proxies miss real value, are easy to game, and can harm organizations.
  2. AI both breaks traditional metrics—making code volume meaningless and often increasing churn and bugs—and widens perception gaps where developers feel faster than measured results show.
  3. A promising path is semantic, context-aware measurement that uses AI to understand what changes actually do and synthesize those findings into simple narratives for leaders, aiming for "good enough" insight that’s harder to game.

Managing for Abundance, not Scarcity

Anant’s Newsletter • 8 implied HN points • 14 Jan 26
🕹 Technology Metrics
  1. Writing code is now cheap because of AI, so the real constraints are context, taste, and decision-making — shift from protecting developer hours to enabling rapid experimentation and customer outcomes.
  2. Middle managers and leaders need to get hands-on and write code; pure people managers should no longer be acceptable, and everyone should be expected to be a builder.
  3. Restructure teams toward a 'diamond' model with more senior builders who can wield AI end-to-end, kill spec-first culture in favor of working prototypes, and measure success by iterations and customer outcomes instead of time estimates.

Lessons from Peaches 🍑

Condensing the Cloud • 176 implied HN points • 28 Mar 23
💼 Business Metrics
  1. Peach prices don't determine taste; price isn't a reliable indicator of quality.
  2. Focus on short-term optimization variables for long-term company success.
  3. Prioritize efficiency and adapt metrics as market environments change.

The Four Anxieties of Engineering Leaders

Maestro's Musings • 140 implied HN points • 02 May 25
💼 Business Metrics
  1. Engineering leaders worry about losing top performers to burnout. These key team members are crucial, and their departure can hurt projects and team morale.
  2. There's a constant push and pull between achieving exceptional results and maintaining a healthy team culture. Leaders need to find a balance that works for everyone on the team.
  3. Most current metrics used to measure engineering success are flawed. They focus on activities rather than real impact, making it hard for leaders to see what's truly happening in their teams.

The Pipeline Metrics That Matter

Bottom Up by David Sacks • 281 implied HN points • 29 Oct 24
💼 Business Metrics
  1. Tracking pipeline generation is crucial for growth in SaaS companies. If new opportunities are increasing, it's a good sign to hire more sales staff; if not, boost marketing efforts.
  2. Understanding pipeline conversion metrics helps identify where improvements are needed. Knowing how long deals take to close and where they tend to get stuck can lead to better sales processes.
  3. Active pipeline metrics allow for accurate forecasting. Keeping an eye on open opportunities and their expected close dates helps businesses plan and strategize effectively.

Turning NPS into action: how to make the most out of a... dubious metric*

UX Psychology • 218 implied HN points • 14 Dec 22
💼 Business Metrics
  1. NPS (Net Promoter Score) measures customer loyalty based on likelihood of recommendation. Responses are categorized into Promoters, Passives, and Detractors.
  2. To make the most of NPS, ensure it is measured properly by defining target audience, using standardized surveys, analyzing data regularly, and avoiding biases.
  3. Despite NPS limitations, leverage its open-ended question for uncovering user pain points, recruiting research participants, involving all team members, complementing with other metrics, and using it strategically.

Clouded Judgement 1.2.26 - Authority Is the AI Bottleneck

Clouded Judgement • 10 implied HN points • 02 Jan 26
💼 Business Metrics
  1. Whether AI is allowed to be authoritative or only assistive decides its real impact: assistive AI saves time but usually doesn’t change results, while authoritative AI can reshape workflows and unlock big returns.
  2. Letting AI act forces organizational choices about where the source of truth is, what error rates are acceptable, who is accountable, and how to roll back mistakes — and those questions matter more than which model you use.
  3. Teams that get outsized returns pick narrow domains, set tight guardrails, and invest in data quality, observability, and rollback so AI can own outcomes and trust grows over time.