Gordon Brander talking about why you should not rebuild software ecosystem. And if you are rebuilding a software ecosystem, you might be screwed.

Software can be rebuilt, because software is a machine. But a software ecosystem is not a machine. It is a living system. When we attempt to rebuild the ecosystem, we’re making a category error. We’re confusing the software for the ecological process unfolding around it.

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You can’t rebuild an ecosystem, just like you can’t rebuild the Amazon rainforest. You can only grow with it, or bulldoze it and start over from zero.

May be that’s why legacy modernisation projects are so complex. Because you are screwed but you don’t know where.

Simon Willison has published his experience on he uses LLMs to write code. It is filled with great tips and nuggets of wisdom. Here are my favourites.

If someone tells you that coding with LLMs is easy they are (probably unintentionally) misleading you. They may well have stumbled on to patterns that work, but those patterns do not come naturally to everyone.

If you assume that this technology will implement your project perfectly without you needing to exercise any of your own skill you’ll quickly be disappointed.

Instead, use them to augment your abilities. My current favorite mental model is to think of them as an over-confident pair programming assistant who’s lightning fast at looking things up, can churn out relevant examples at a moment’s notice and can execute on tedious tasks without complaint.

A crucial characteristic of any model is its training cut-off date. This is the date at which the data they were trained on stopped being collected. For OpenAI’s models this is usually October of 2023. Anthropic and Gemini and other providers may have more recent dates.

This is extremely important for code, because it influences what libraries they will be familiar with. If the library you are using had a major breaking change since October 2023, OpenAI models won’t know about it!

I find LLMs respond extremely well to function signatures like the one I use here. I get to act as the function designer, the LLM does the work of building the body to my specification.

Your responsibility as a software developer is to deliver working systems. If you haven’t seen it run, it’s not a working system. You need to invest in strengthening those manual QA habits.

it’s not about getting work done faster, it’s about being able to ship projects that I wouldn’t have been able to justify spending time on at all.

And my favourite.

LLMs amplify existing expertise

While the jury is still out there on buying the dip, Nick Maggiulli explains why buying the dip—especially during recession—might not be possible for everyone. 

If we assume that the market will eventually recover, then a decline in equity prices today allows young and “asset-light” investors to buy cheaper today and earn higher returns in the future.

But the problem with this logic is that all else isn’t equal. Market crashes don’t happen in a vacuum. When asset prices decline, economic consequences typically follow. Workers lose their jobs or don’t get promoted. Hiring freezes up. People stop spending as much money. And this negative cycle feeds on itself.

If you happen to be someone who keeps their high-paying job during such a time, then, yes, a market decline can be a buying opportunity. But this isn’t the case for everyone. In fact, the paper The Short- and Long-Term Career Effects of Graduating in a Recession suggests that those who start their career during a recession tend to see 5% lower lifetime earnings. As the authors state:

A typical recession—a rise in unemployment rates by 5 percentage points in our context—implies an initial loss in earnings of about 9 percent that halves within 5 years, and finally fades to 0 by 10 years. For this time period, these reductions add up to a loss of about 5 percent of cumulated earnings.

I know what you might be thinking: “Yes, I lose 5% of my lifetime earnings, but I get to buy stocks at a 20%+ discount. How is that not a huge win?”

There are a few problems with this thinking, each of which I will address in turn.

Eurasia Review talking about the rise of Services as Software. 

The traditional Software-as-a-Service (SaaS) model disrupted enterprise Information Technology (IT) by replacing expensive, on-premise software solutions with cloud-based applications. Databases were maintained by the SaaS providers remotely, and the per-seat license model evolved rapidly to annuity payments and the rise of Annualised Recurring Revenue (ARR). SaaS has dominated the technology world for the better part of two decades. Today, AI is pushing the envelope by turning services built to be used by humans as ‘self-serve’ utilities into automatically-running software solutions that execute autonomously—a paradigm shift the venture capital world, in particular, has termed ‘Services as Software’.

A little later in the article. 

The AI-driven shift brings into question the traditional notion of availing an ‘expert service’. Software development, legal, and financial services are all coveted industries where workers are considered ‘experts’ delivering specialised services. The human role will undergo tremendous redefinition and will require calibrated re-skilling.

Phillip Carter talking about impact of AI on jobs.

A lot of dumbasses in company leadership see AI and salivate at the idea of reducing headcount so “AI can do the work”. This is clearly a fear that a lot of people who earn paychecks for a living have. I have two thoughts on this topic:

Firstly, if you’re a company leader who sees a wave as large as the introduction of the computer coming and your thought is to “use less resources to do the same work”, you’re an uncreative hack and it’s you who deserves to be fired. The goal should be how you can accomplish more when you have cognitive co-processors at your disposal.

Secondly, it is undeniable that a shift will occur and with that there will be damage done. A lot of people are uninterested in learning new skills for work because work is just … work. It’s their means to earn a paycheck so they can do what they actually care about. I won’t judge that behavior because it’s not inherently right or wrong. But I will say that if you don’t want to be caught with your pants down when your workplace does expect you to do more and different things with this technology, there’s no better time than now to start learning how to use it.

The second paragraph is similar to the reasoning of Dustin Ewers, where he argues that AI will create more software jobs rather than eliminate them.

And, this gives me hope.

This is probably the first article I have read on the economics of using AI for development. Vikram Sreekanti and Joseph E. Gonzalez talk about their experience of using Devin for a month. 

When Devin works, the economics of using it are pretty good. You currently pay $500 for 250 ACUs, and the small tasks that Devin succeeded at took 1-5 ACUs ($2-10). Paying a few dollars to fix small bugs and save even just one hour per-bug is a great tradeoff — one that we would make any day of the week. The issue is that there’s a very narrow set of tasks that are long enough to require an engineer to context switch and short enough to be in Devin’s working window.

When Devin doesn’t work, the economics start to look suspect. The 3 bigger tasks we tried averaged about 20 ACUs and 2 of the 3 didn’t yield usable results. While $40 would be extremely cheap for implementing these larger tasks, our (to be fair, limited) sample indicates that these larger tasks consume a disproportional number of ACUs — these tasks weren’t 5-10x harder than the smaller ones that succeeded. More importantly, they often fail, so you get nothing for your $40.

The last statement is crucial. If you pay a developer $40 and they don’t deliver, you have the option to go back and say, “Hey, this isn’t what I wanted. I expected…”—and still get value for your money.

But with AI, if you spend $40 and it doesn’t deliver then that money is gone. Poof!

That said, I don’t want to get carried away. What if, a year from now, AI actually starts delivering!

Noah Smith reflecting on the recent meeting between Donald Trump and Volodymyr Zelensky. This is a paid article—which I do not have access to—but the below paragraph caught my eye.

The world is not made up of heroes and villains, like in Star Wars or a Marvel movie. Instead, like the Game of Thrones universe or a dark edgy comic book, the world is made up of antiheroes and villains. The kindest person you ever meet will have some moments of cruelty in their life; even the most upright and honest bend the rules once in a while; even people fighting for noble causes will have times when they’re selfish, arrogant, and greedy.

I previously read and liked M. Pattabiraman’s thoughts on financial independence.

Morgan Housel writes about independence and offers a another perspective on financial independence.

5. Financial independence doesn’t mean you stop working.

This idea is related to the previous one: Financial independence is a wonderful goal. But achieving it doesn’t necessarily mean you stop working – just that you choose the work you do, when you do it, for how long, and whom you do it with.

Those who retire early tend to come from one of two camps:

They hated their work but kept doing it to make as much money as they could.

They enjoyed their work but quit when they had enough money.

To each their own, but both look like situations where money controls your decisions. The irony is that some people who think they’re financially independent are actually completely dependent on money, so much so that they spend their days doing things they’d rather not because money tells them they should. Rather than using money as a tool, the money used them.

When I first started investing in equities, I decided to follow buy and hold strategy. I will buy quality companies and hold them for long term. There will be periodic reviews and some exceptions, but more or less very limited selling. Rather, slowly build position in quality companies. 

Thanks to Birla, this strategy is now being put to the test.

Birla first targeted Asian Paints with the launch of Birla Opus Paints. The mere announcement of their entry into the paints business—and their subsequent doubling of investment—sent Asian Paints’ stock price tumbling. And with it, my returns in Asian Paints. Asian Paints is part of my buy and hold portfolio, a decision which was made looking in the rear view mirror. Not the best way to make investing decisions.

And today, Birla announced that they will be entering wires and cables business, directly competing with Havells and Polycab—two stock I own. Both, Havells and Polycab, have been consistent outperformers against Nifty indices, though my investment in them was relatively small. But it still stings that this news wiped off 6% and 18% of their market caps, respectively. I stayed put with Polycab even amid reports of a ₹200 crore tax evasion. But Birla’s latest move unnerves me.

I thought buy and hold will be simple. But it is now that I realise—in buy and hold, taking no action is also an action in itself. And more often than not, you will be taking no action.

A sensible discussion on The Morning Brief podcast between Anirban Chowdhury and Nishanth Vasudevan on the FPI sell off. They also discuss some strategies for you to navigate the current market.

If you look at the price to earnings ratio, which is a very widely followed valuation parameter, that has kind of come closer to the 10-year average or it has kind of fallen slightly below the 10-year average, which basically shows that valuation among large caps, those have kind of eased quite a bit and they are looking much better in terms of valuations. But now when we look at the smaller companies, the small and mid-cap companies, the valuations who are there, they are still much above the 10-year average. Even despite all the correction.

 …

Despite that, many of the stocks are still trading above their averages. And yeah, there is still a fair bit of valuation concern in many of them. And that is the same point which ICICI Prudential, CIO S Naren raised.

He said that in a recent conference, where he said that the appetite for small and mid cap stocks, they have not subsided. People are still doing a lot of SIPs in that. And that is where he warned that you can’t do SIP, a systematic investment plan in an overvalued asset class.

In that, he actually was eluding to small and mid cap stocks. So over there, his suggestion was that, if at all you want to do a SIP, you should go for large cap oriented schemes or large cap oriented stocks.