January 15th, 2026

​1. SaaS METRIC OF THE WEEK: Fundraising Metrics. Make your fundraising way less chaotic by getting these metrics dialed in. Unless you are pre-revenue, Investors will expect to see detailed ARR, CAC, LTV, retention rates, and engagement metrics. A strong data deck (or data room) can answer investors' questions and show a clear path to growth.

2. PRICING: Kicking off this new year right with some pricing upgrade levers that may actually work for ya. You can kill monthly billing to reduce early churn on agentic products; Remove seat limits but tighten usage caps tied to value; Raise entry-tier pricing to "encourage" upgrades.

3. CAPITAL: Oh! Is your AI stack quietly funded by junk bonds? Tom Tunguz breaks down how hyperscalers are leaning hard on debt to finance their AI capex - the AI biz model here is seriously mad, commodity-based products that need tens of billions in data center, GPU, and power financing- and what happens if growth slows before cash flows catch up?

4. BRAND vs DEMAND: In a recent survey, 168 B2B CMOs say brand matters, but the reality is that their budgets don't back that up. Actual spend sits at ~70% demand / ~25–30% brand, even though the ideal mix looks closer to 50% / 40%. 73% believe brand makes demand more efficient, yet only 28% can tie their brand to pipeline - so when cuts come, 55% protect demand and just 11% protect brand. Which brings us to the second part: reach is a brand-based challenge. Brand expands the pool; demand converts it - nice little sales tech-ism for the week.

5. EDUCATION: A follow-up from all of the above (2-4) - Clouded Judgement makes a sharp point most AI startups miss: education IS the go-to-market (see #4 above). Buyers don’t know what to build, let alone buy (see #3 for that). The winners teach the market which problems matter, how they should be solved, and why their worldview is right. Free tiers, sandboxes, fast time-to-value aren’t growth hacks - they’re education engines (see #2). Until customers learn by doing, demand stalls or churns.

6. LEADERSHIP: When you take a look around, most leaders perform with certainty. This article argues that it’s a risk. The best leaders run leadership similar to GTM teams: small experiments, fast feedback, public learning. Shorter cycles beat perfect plans, curiosity beats confidence (and IMO teams trust you more when you stop pretending you have the answers).

7. DEV: Has the cost of shipping software dropped due to AI? This piece makes a serious case that agentic coding collapses implementation time, not thinking time. Month-long internal tools now ship in days. Coordination overhead disappears. $50k builds become $5k problems. The real moat isn’t necessarily the code anymore - it’s domain knowledge plus taste. And don't forget - all those people with knowledge have to come up the ranks somewhere.

8. SYSTEM OF RECORDS: Another Clouded Judgement article, and this is my wheelhouse, so this spoke to me - sure AI is cool - but  the harder automation gets, the more enterprises need a hard core (and un-cool) source of truth that agents can reliably read/write. Systems of record don’t disappear; they get embedded as the truth layers that govern agent workflows and outputs.

9. REQUIREMENTS: This is also my wheelhouse, and I'm sure it's the same for many of you B2B-SaaS operators. Most projects/implementations don’t exactly start with clarity, but they do start with intent. This product-focused article argues the real skill isn’t forcing certainty early, it’s moving forward without pretending (I call it holding hands in the fog). Progressive elaboration and rolling-wave planning let you extract the signals from complexity, commit where you can, and deliberately leave the rest provisional/in the backlog. It’s a great article to frame how you can create momentum without boxing yourself into poor decisions or plans.

10. CASE STUDY: Series B+ raises. Most of us should be so lucky to get to this stage, but how do you raise funds beyond Series B (roughly 15% that raise seed make it to Series B). Scale Ventures’ Stacey Bishop gives the lowdown.

POD OF THE WEEK: Two enterprise AI operators who’ve shipped 50+ AI products (across OpenAI, Google, Amazon, and Databricks) break down what actually works when building and scaling AI.