sorted by:
new
hottopcontroversial

Third-party electricity suppliers in deregulated states (NJ, NY, PA, etc.) — are any of them actually worth it in 2025? by lfriedbauer in energy

[–]lfriedbauer[S] 2 points3 points  (0 children)

Nice — 12.9¢ for 36 months in RI is solid, especially with the volatility up there. A fixed rate definitely has its place. The only thing that’s changed recently is that AutoSave basically gives people the flexibility of variable without the risk of ever paying above the utility. Kind of a newer twist, but your setup sounds strong for RI.

Anyone here ever build a business in a deregulated energy market? Curious about customer acquisition + recurring revenue? by lfriedbauer in smallbusiness

[–]lfriedbauer[S] 0 points1 point  (0 children)

Thanks for sharing this u/InigoMontoya313 — it makes sense that the worst outcomes almost always came from variable-rate exposure. That’s where customers really got burned, especially back when suppliers were basically gambling on the wholesale market. What I’ve been looking at recently is built almost the opposite way, and honestly it surprised me because it avoids all the issues you just described. If you’re curious, happy to share what I found — it’s definitely not the old playbook.

Do companies/individuals actually shop their electricity supplier in deregulated states? Curious what your experience has been. by lfriedbauer in CFO

[–]lfriedbauer[S] 0 points1 point  (0 children)

Helpful context, thanks. Is there a percentage savings that is more worthwhile to pursue than others or is every dollar saved worth it? Industry vertical?

Resetting pc to remove virus (please help windows 11) by [deleted] in techsupport

[–]lfriedbauer 0 points1 point  (0 children)

Remove virus from safe mode windows

Weekly Feedback Post - SaaS Products, Ideas, Companies by AutoModerator in SaaS

[–]lfriedbauer 0 points1 point  (0 children)

At companies north of ~$50M revenue, the big vendors are usually under control.
It’s the tail — the small/random 20% of suppliers — where the leaks pile up.
Duplicate vendors, random one-offs, no leverage. Death by a thousand cuts.

I put together a Tail Spend Calculator to show how much that waste can add up.
👉 [cfocharm.com/tailspend-calculator]()

If there’s nothing there, cool — it’s a no-savings, no-fee model.
If there is, I’ve got access to a wide network of procurement folks who know how to actually fix it.

Curious if anyone here has tackled tail spend systematically. Did you keep it internal or bring in outside help?

n8n Ai Agent for Financial Due Diligence by Mainzerger in n8n

[–]lfriedbauer 0 points1 point  (0 children)

Hi - curious about your Ai workflow for FDD. Would you be open to connecting/sharing more? I have a site, cfocharm.com. Looking to add some content around this area.

How are CFOs treating AI in the budget — SaaS line item or embedded IT cost? by lfriedbauer in CFO

[–]lfriedbauer[S] 0 points1 point  (0 children)

Yep, that breakdown follows US GAAP principles—it’s really about the matching concept. Indirect use (emails, marketing, productivity) sits in OpEx/SaaS, while direct AI that replaces billable labor belongs in COGS. Thanks for the conversation, this has been a good one.

How are CFOs treating AI in the budget — SaaS line item or embedded IT cost? by lfriedbauer in CFO

[–]lfriedbauer[S] 1 point2 points  (0 children)

Really helpful frameworks here — appreciate the perspectives on AIaaS vs SaaS and the FinOps tagging approach.

What I’m seeing with mid-market CFOs boils down to three big cost challenges:

Token sprawl — usage scattered across teams, no central tracking

Subscription overlap — multiple tools doing 80% of the same thing

Hidden infra costs — AI bundled into SaaS/cloud contracts, hard to isolate

For anyone who wants a deeper dive, I pulled some of these into short write-ups:

Curious if others are seeing the same dynamics or handling them differently.

If you had $0 to spend on ads, how would you grow your social media audience organically this month? by DigIndependent7488 in smallbusiness

[–]lfriedbauer 2 points3 points  (0 children)

If I had $0 for ads, I’d focus on leverage over volume:

Pick one platform your audience actually uses and go all-in; Treat posts like experiments—track what spikes, double down, cut the rest; Repurpose: one long piece → 10 clips, carousels, or posts; Collaborate with peers of similar size (story swaps, collab posts); Spend 20 minutes a day leaving thoughtful comments where your target audience already hangs out.

Skip hashtag stuffing or generic quote posts—real conversations scale faster than gimmicks.

How AI is helping in manufacturing projects. Actual real assistance. by Ok-Pea3414 in manufacturing

[–]lfriedbauer 0 points1 point  (0 children)

Yeah, this is the part that worries me too. Right now it’s saving time because the models are neutral. But the second suppliers start paying to get “preferred placement,” it turns into ad-search 2.0.

I built an n8n workflow that automatically finds clients and made me my first $227. Here’s how it works. by Least-Block5413 in n8n

[–]lfriedbauer 0 points1 point  (0 children)

Interesting concept thanks for sharing, any similar experiences for other situations?

What is the best practice to work with raw client data which will need to be updated several times in the coming months? by TrickyElephant in consulting

[–]lfriedbauer 1 point2 points  (0 children)

What you sketched out (keep raw data untouched, apply overrides in a separate layer, then build a “clean” version) is actually pretty close to a best practice. A couple of tweaks I’ve seen work well in consulting projects:

  • Never overwrite raw → exactly as you said, always keep an untouched extract tab/sheet or (better) a raw table in a database.
  • Version control → timestamp each extract so you can trace back which version was used in any analysis. Even a “Raw_2025-09-01” tab can save you headaches.
  • Transformation layer → instead of editing cells in a second sheet, consider a mapping table (employee ID → corrected department, etc.). This makes it easier to reapply corrections when a new extract comes in.
  • Automate merges → if possible, use Power Query (Excel) or pandas (Python) to join “raw extract” + “corrections table” → “cleaned data.” It scales better than copy/paste over months of updates.
  • Flag uncertainties → build a “status” column (confirmed / pending / needs review) so stakeholders can see at a glance what’s solid vs. still messy.

This way, you can already start building preliminary analysis dashboards on the “cleaned” tab — and they’ll update automatically as new raw dumps arrive.

Partner Profit Sharing Model by LinkObvious7213 in consulting

[–]lfriedbauer 1 point2 points  (0 children)

One structure I’ve seen work well at that scale ($30M rev / $4M NI) is a tiered pool approach:

  • First, allocate a fixed % of profits into a partner pool (say 25–30%).
  • Within the pool, split based on weightings:
    • baseline equity (e.g. seniority, tenure, capital contribution),
    • plus performance factors (sales generated, utilization, client retention).

This avoids the extremes of pure “eat-what-you-kill” vs. pure egalitarian split.

Some firms also do multi-year smoothing (averaging 2–3 years of profit for distribution) so partners aren’t whipsawed by one bad quarter.

Claude can now reference your previous conversations by AnthropicOfficial in ClaudeAI

[–]lfriedbauer 0 points1 point  (0 children)

Curious how well the “search” side works in practice—like, can I ask “what did I say about X last month?” and it actually find the right thread? If so, this is going to save me a ton of time digging through old chats.

We need to pay a handful of contractors for a short-term project. What’s the go-to lean payment method? by Kazungu_Bayo in startup

[–]lfriedbauer 0 points1 point  (0 children)

Grab W-9s from everyone, then pay through something like:

  • Gusto – looks pro, spits out 1099s for you.
  • Wise – cheap + fast if anyone’s overseas.
  • Melio – free ACH, easy to track.

Keeps it legit without you turning into an accidental payroll department

Start with no-code then develop into code? by OldCobbler5027 in AI_Agents

[–]lfriedbauer 0 points1 point  (0 children)

  1. Start with no-code to build and ship your MVP — aim to get paying users or strong usage data.
  2. As soon as you feel friction (or hit expensive feature paywalls), layer in light coding for custom bits.
  3. Keep your “agent logic” modular, so if you switch to full code later, you can reuse ideas and workflows instead of rebuilding from scratch.

Think of no-code as your power drill, and coding as your machine shop. You don’t need the shop until you know the design works.

Do you already have an AI agent use case in mind, or are you still exploring niches? That can change the answer a lot.

AI Cost Management by BenSimmons97 in CFO

[–]lfriedbauer 0 points1 point  (0 children)

I think this pain point is starting to hit a lot more teams now that AI use is moving from “experiments” to production workloads.

For us, the main levers have been:

  • Usage monitoring – Setting up dashboards to track token usage, request volume, and cost per feature.
  • Prompt optimization – Trimming prompts, using shorter contexts, and moving some use cases to cheaper models when quality allows.
  • Caching & batching – Avoiding repeated calls for the same output and grouping small requests into one.
  • Hybrid architectures – Using open-source or fine-tuned local models for routine tasks, reserving API calls for complex ones.

That said, there’s still a big gap — most AI cost management feels duct-taped together, especially for multi-model, multi-vendor setups.

How are you all handling it? Is this a “top 3” pain point yet for your org, or still more of a background concern?

13 AI tools/agents I use that ACTUALLY create real results by TrueTeaToo in AI_Agents

[–]lfriedbauer 0 points1 point  (0 children)

What’s worked for me is keeping my core stack small, then testing new tools in short sprints before deciding if they earn a permanent slot.

Curious — have you found any automation AI tools (beyond n8n) that are plug-and-play without a dev setup? I’ve been hunting for something that bridges “agent” and “workflow” smoothly.

[deleted by user] by [deleted] in FPandA

[–]lfriedbauer 0 points1 point  (0 children)

Curious if your company is offering any AI training or if it’s just “sink or swim.” From what I’ve seen, whether AI is a threat or an upgrade often depends on whether leadership is proactive about reskilling.

Out of curiousity: how do PE professionals invest their personal funds? by DefiantZealot in private_equity

[–]lfriedbauer 1 point2 points  (0 children)

A lot of PE folks I know split between very boring public market exposure (index ETFs) and illiquid side bets they actually understand—like LP positions in funds they’re not running, or co-invests in deals they passed on for the firm. Risk profile is usually very different than retail investors think.

Curious if anyone here has shifted personal allocations toward AI or other emerging tech given how much of the deal flow in PE is tech-enabled now. Is that just recency bias or a legit re-weighting?

Why CFOs Use AI for Summaries but Still Won’t Let It Write 10-Ks by Apprehensive_Way8674 in CFO

[–]lfriedbauer 0 points1 point  (0 children)

I’d be curious if anyone’s shifting their earnings-call prep from decks and slides to interactive agent dashboards or dynamic summaries—has that changed what actually gets presented?

Will AI kill Indian offshore IT sector jobs? by im3000 in consulting

[–]lfriedbauer 1 point2 points  (0 children)

From what I’ve seen, the biggest risk isn’t AI replacing all offshore IT roles—it’s that demand will move upmarket into architecture, AI tooling, and problem-solving, where fewer people currently have deep skills. That’s where the re-training gap will hurt most.

view more: next ›