#brightplace launched Direct on Sept. 29: apartment sites built for search and AI discovery, with live pricing and availability.
My take: stale property data is becoming a marketing problem, too.
#CRE #PropTech #AI
brightplace.ai/news/brightpl…
FSS’s Sept. 30 AI release matches incoming files to document requests for fiduciaries.
A useful idea for CRE intake: track what each file satisfies, not just how many files arrived.
#CRE #AI #DocumentAutomation
tinyurl.com/24k3rd8x
Levelpath’s Sept. 30 Ranger launch says AI can answer across 10,000 contracts with citations.
It is procurement software. The CRE lesson: test whether the cited clause actually supports the answer.
#CRE #AI #Levelpath
businesswire.com/news/home/2…
Apparently, my version of retirement involves 16-hour days of writing code.
At 69, I got obsessed with AI and built a portal for my own property portfolio. That became REOI™.
Ever been that absorbed in building something?
#Claude #ClaudeCode #CRE
Would you trust AI with your property documents?
I’m fascinated by AI. I also want to see where an answer comes from.
That’s why source references matter in REOI™.
What would you need to see before trusting an AI answer?
#Claude #ClaudeCode #CRE
If you own a property, what do you wish you could see on one screen?
I built REOI™ for my own portfolio: documents, obligations, deadlines and questions that need my attention.
What would be on your screen?
#Claude #ClaudeCode #CRE
Does this count as retirement?
At 69, I fell in love with AI. Three months, 16 hours a day: I architected and coded a portal for my own property portfolio.
I found it so useful I built a company around it: REOI™.
reo-intel.com
What do you think?
AppFolio’s Sept. 29 Realm-X release adds a knowledge base for customer documents and policies.
My take: property AI is moving closer to the records teams already use. As REOI™ founder, I welcome the focus on evidence.
#CRE #AI #AppFolio
tinyurl.com/283o4xgk
Tango reports 89% of surveyed large retailers use AI in lease decisions or processes (Sept. 14; 200+ locations).
Adoption is already substantial in this group. The next buying question: can I verify the answer?
#CRE #AI
tangoanalytics.com/blog/ai-l…
DealWise AI added rent-reconciliation checks on Sept. 16.
My takeaway: faster model-building needs a checking step. Ask the demo to find a mismatch, then show how to verify it against the rent schedule.
#CRE #PropTech
dealwiseai.com/whats-new
What property question sends you back into the files?
A renewal date? A lease amendment? How tenant options line up with the loan?
Try REOI on one property. Give us the folder link; we'll handle setup.
Reply with what you'd like to test.
reo-intel.com
Grotto reports Hillpointe cut new leasing staff training from 90 days to 9 with AI coaching (Sept. 23).
That could change onboarding costs. Before using it in a budget, ask what “ready” means and how it was measured.
#CRE #AI
tinyurl.com/26g7hr2x
A lease ends. A loan matures. How much time is between them?
REOI brings tenant decisions, rate resets and loan maturities onto one timeline.
Explore the sample: reo-intel.com/sample
Names and amounts changed. Figures reflect the assessment date.
Already have a system that works? Keep it.
Try REOI alongside it on one property. Send us the folder link; we'll handle setup and review the results with you.
Did it answer a question that still takes work today?
Message me to try it.
reo-intel.com
Funnel’s Sept. 22 Fenix AI announcement connects AI with external systems.
For operators, the value is in completed workflows across existing tools. My demo test: follow one renter request from start to finish.
#CRE #AI
tinyurl.com/27e342fu
One property. One folder link.
Give us the link and sit back. We'll set up your REOI assessment and walk through the results with you.
I'm inviting founding clients to try it and give candid feedback. Message me to take part.
Take a look: reo-intel.com
Yardi’s Sept. 3 Virtuoso announcement puts AI into resident questions, work orders and invoice approvals.
My take: choosing the software now includes deciding what it may do alone and when a person must approve.
#CRE #AI
tinyurl.com/2xtyy9hz
One property. One link. We’ll take it from here.
Try REOI™ alongside your existing system. Share your property documents; no sorting or retyping. Review the results with us and give candid feedback.
Interested in becoming a founding client? Message me.
#CRE
Moshe Ovadya retweeted
A few random notes from claude coding quite a bit last few weeks.
Coding workflow. Given the latest lift in LLM coding capability, like many others I rapidly went from about 80% manual+autocomplete coding and 20% agents in November to 80% agent coding and 20% edits+touchups in December. i.e. I really am mostly programming in English now, a bit sheepishly telling the LLM what code to write... in words. It hurts the ego a bit but the power to operate over software in large "code actions" is just too net useful, especially once you adapt to it, configure it, learn to use it, and wrap your head around what it can and cannot do. This is easily the biggest change to my basic coding workflow in ~2 decades of programming and it happened over the course of a few weeks. I'd expect something similar to be happening to well into double digit percent of engineers out there, while the awareness of it in the general population feels well into low single digit percent.
IDEs/agent swarms/fallability. Both the "no need for IDE anymore" hype and the "agent swarm" hype is imo too much for right now. The models definitely still make mistakes and if you have any code you actually care about I would watch them like a hawk, in a nice large IDE on the side. The mistakes have changed a lot - they are not simple syntax errors anymore, they are subtle conceptual errors that a slightly sloppy, hasty junior dev might do. The most common category is that the models make wrong assumptions on your behalf and just run along with them without checking. They also don't manage their confusion, they don't seek clarifications, they don't surface inconsistencies, they don't present tradeoffs, they don't push back when they should, and they are still a little too sycophantic. Things get better in plan mode, but there is some need for a lightweight inline plan mode. They also really like to overcomplicate code and APIs, they bloat abstractions, they don't clean up dead code after themselves, etc. They will implement an inefficient, bloated, brittle construction over 1000 lines of code and it's up to you to be like "umm couldn't you just do this instead?" and they will be like "of course!" and immediately cut it down to 100 lines. They still sometimes change/remove comments and code they don't like or don't sufficiently understand as side effects, even if it is orthogonal to the task at hand. All of this happens despite a few simple attempts to fix it via instructions in CLAUDE . md. Despite all these issues, it is still a net huge improvement and it's very difficult to imagine going back to manual coding. TLDR everyone has their developing flow, my current is a small few CC sessions on the left in ghostty windows/tabs and an IDE on the right for viewing the code + manual edits.
Tenacity. It's so interesting to watch an agent relentlessly work at something. They never get tired, they never get demoralized, they just keep going and trying things where a person would have given up long ago to fight another day. It's a "feel the AGI" moment to watch it struggle with something for a long time just to come out victorious 30 minutes later. You realize that stamina is a core bottleneck to work and that with LLMs in hand it has been dramatically increased.
Speedups. It's not clear how to measure the "speedup" of LLM assistance. Certainly I feel net way faster at what I was going to do, but the main effect is that I do a lot more than I was going to do because 1) I can code up all kinds of things that just wouldn't have been worth coding before and 2) I can approach code that I couldn't work on before because of knowledge/skill issue. So certainly it's speedup, but it's possibly a lot more an expansion.
Leverage. LLMs are exceptionally good at looping until they meet specific goals and this is where most of the "feel the AGI" magic is to be found. Don't tell it what to do, give it success criteria and watch it go. Get it to write tests first and then pass them. Put it in the loop with a browser MCP. Write the naive algorithm that is very likely correct first, then ask it to optimize it while preserving correctness. Change your approach from imperative to declarative to get the agents looping longer and gain leverage.
Fun. I didn't anticipate that with agents programming feels *more* fun because a lot of the fill in the blanks drudgery is removed and what remains is the creative part. I also feel less blocked/stuck (which is not fun) and I experience a lot more courage because there's almost always a way to work hand in hand with it to make some positive progress. I have seen the opposite sentiment from other people too; LLM coding will split up engineers based on those who primarily liked coding and those who primarily liked building.
Atrophy. I've already noticed that I am slowly starting to atrophy my ability to write code manually. Generation (writing code) and discrimination (reading code) are different capabilities in the brain. Largely due to all the little mostly syntactic details involved in programming, you can review code just fine even if you struggle to write it.
Slopacolypse. I am bracing for 2026 as the year of the slopacolypse across all of github, substack, arxiv, X/instagram, and generally all digital media. We're also going to see a lot more AI hype productivity theater (is that even possible?), on the side of actual, real improvements.
Questions. A few of the questions on my mind:
- What happens to the "10X engineer" - the ratio of productivity between the mean and the max engineer? It's quite possible that this grows *a lot*.
- Armed with LLMs, do generalists increasingly outperform specialists? LLMs are a lot better at fill in the blanks (the micro) than grand strategy (the macro).
- What does LLM coding feel like in the future? Is it like playing StarCraft? Playing Factorio? Playing music?
- How much of society is bottlenecked by digital knowledge work?
TLDR Where does this leave us? LLM agent capabilities (Claude & Codex especially) have crossed some kind of threshold of coherence around December 2025 and caused a phase shift in software engineering and closely related. The intelligence part suddenly feels quite a bit ahead of all the rest of it - integrations (tools, knowledge), the necessity for new organizational workflows, processes, diffusion more generally. 2026 is going to be a high energy year as the industry metabolizes the new capability.
















