Issue 003 · AI interconnect

That last question is the whole case. Amphenol and TE sell into the same racks, to the same buyers, yet Amphenol trades at 32 times forward earnings and TE at 18. The spread has stayed open long enough that the “second-source discount” is starting to look less like a discount than a misprint.

On the base case we are close to the Street. Where we differ is the shape of the distribution around it.

The weighted $262 is almost exactly the Street’s consensus: a $262 average, a $190 to $302 range, and a Buy rating. We agree on the base. Where we part company is the spread. We think the re-rating optionality in the bull case ($357) is underpriced, and that the floor sits higher than the Street’s $190 low. The drivers behind these numbers sit in the bridge table in section seven, and they are worth reading before the targets.

That one sentence carries both the bull case and the main risk. (The rack is the cabinet that holds a cluster of GPUs and wires them together into a single machine; copper is the short, fast link inside it.) On the bull side, copper is still the dominant in-rack link, demand is strong enough that the company is already booking 2027, and the orders are real: a record $5.3B in Q2 at a book-to-bill of 1.12. On the risk side, Curtin reaches for “copper and optical” in the same breath, and TE has just bought into leading-edge optical technology to widen its roadmap. The hedge tells you the optics question is live. So the investment case turns on how much of the company is the copper workhorse, and how much has to become the optical hedge.

AI runs on a physical supply chain. The layers below are the chokepoints atlas: L0 at the base (raw materials) up to L8 (the apps people pay for). Red layers are real chokepoints, meaning one or two suppliers, one region, or multi-year lead times. TE sells at L4, in high-speed connectors and cable. That is a genuine chokepoint, but a shared one: TE and Amphenol both supply it, so TE owns half of the bottleneck rather than all of it.

In-rack copper for scale-up systems is close to a duopoly. Amphenol and TE supply most of it, and you cannot build a dense GPU rack without it. Optics will take the longer links between racks; copper holds the short, fast links inside the rack. For an investor the distinction matters, because TE owns half of a chokepoint rather than a monopoly. Its edge is price, not a moat nobody else has. No third credible supplier has broken in at the leading edge, so the duopoly itself is the protection, and the second seat inside it is what you are buying at a discount.

The investment case stands or falls on the product, so it is worth understanding how a connector actually works. A connector joins two segments of wire or two circuit boards so an electrical signal can pass between them, reliably and cheaply at scale. The hard part in a modern AI server is that the signals are very-high-frequency analogue waveforms running at tens of gigabits per second, and the connector has to preserve the shape of those waveforms as they pass through. If the signal degrades, the GPU at the other end receives a corrupted bit.

Stopping that is signal-integrity engineering, and it is genuinely difficult: pin geometry, the dielectric around the pins, how the cable is terminated, how the assembly is routed inside the rack. The big AI platforms need three things in particular:

The canonical example is Nvidia’s GB200 NVL72 rack, which wires together its 72 GPUs with about 5,000 copper NVLink cables. The design is copper rather than optical because an all-optical version would draw far more power. Over the distances inside a single rack, copper wins on the things that decide the design: cheaper per port, lower latency, lower power.

Once a connector is designed into a platform, it tends to stay. The hyperscaler qualification cycle is long, running through electrical simulation, mechanical and thermal testing, pilot builds, and then full production, and it can take well over a year. After that the connector ships for the life of the platform. A customer will not swap a qualified connector for a cheaper one lightly, because the connector is a tiny fraction of the cost of the rack and the cost of getting it wrong is enormous. That is the moat, and it is structural: a multi-year qualification cycle and a track record on the platforms that matter, rather than a brand or a patent.

The argument between bulls and bears is copper versus optics, and really it is an argument about where the line between them sits. Consensus today puts it at the edge of the rack. The risk is that the line moves inward over time, and that risk now has a date on it. Nvidia plans optical scale-up for systems of more than 1,000 GPUs by about 2028, and has invested billions in optical suppliers. Copper is expected to stay the in-rack workhorse through the near-term Vera Rubin generation in 2026 and 2027. TE’s answer is that it is not a pure copper bet; it has bought leading-edge optical technology to strengthen its passive optical roadmap. The hedge is real, and it costs the bull case some of its simplicity.

TE makes connectors and sensors. Those two words cover an enormous range of products: the small terminals inside a car dashboard, the heavy blocks that route power through a factory, and the precision backplanes and DAC cables that link GPUs inside a server rack. The lineage runs back to 1941, when AMP Incorporated was founded in Pennsylvania. It was spun out of Tyco in 2007, renamed TE Connectivity in 2011, and later redomiciled to Ireland, which is where the “plc” comes from. It employs about 90,000 people across roughly 130 countries.

1941

AMP founded

in Pennsylvania, building the early connector industry around automotive and industrial customers.

1999

AMP acquired by Tyco International

, folded into a diversified conglomerate.

JUL 2007

Tyco break-up.

The connectivity business is spun off as Tyco Electronics.

MAR 2011

Renamed TE Connectivity.

NYSE-listed, with industrial and transportation as its twin pillars. Later redomiciled to Ireland.

2010s

The auto franchise.

Sensor and connector content rises as cars electrify, and TE becomes a backbone supplier to global auto platforms.

2026

AI acceleration.

DDN orders up about 60% YoY, AI applications around 70% of the segment, and the full-year AI revenue target raised mid-year.

Today TE sells into three places: cars (the Transportation segment, mostly automotive sensors and harnesses), factories (industrial automation, energy, aerospace), and data centres (the Digital Data Networks unit inside Industrial). The split between the first two and the third is what defines the investment case.

One half is accelerating and the other is flat. The blended company grew 7% organic, and the market prices the blend rather than the half that is winning. The opportunity is in that gap.

The model is simple to describe and hard to compete with.

1 · Design in

TE’s engineers specify a connector, backplane or cable for the customer’s AI server, car or factory system, to electrical, mechanical, thermal and cost targets.

2 · Qualify

The part runs the customer’s qualification cycle: signal-integrity and reliability testing, then pilot builds. Often more than a year for a new AI platform.

3 · Ship for life

Once designed in, it ships in production volume for the life of the platform. Volume is visible, because orders track the customer’s build plan.

4 · Content rises

Each GPU generation uses more high-speed links per rack. Even when the unit price falls, the content per rack rises.

The flywheel is the whole model, and the hard part is the front of it. The segment numbers show the cycle in action: Industrial, which contains DDN, was up 27% reported, with DDN itself up 46% organic, while Transportation was down 0.5% organic.

DDN is the reason to look at the stock now. The unit sits inside Industrial and houses TE’s data-centre and AI business: the high-speed connectors, cable assemblies and backplanes used inside AI server racks.

The macro picture is simple. Hyperscalers are still building AI capacity faster than the supply chain can keep up, and TE is one of only two suppliers they can call. TE raised its $2.4B AI target mid-year rather than setting it at the start, and Curtin said the orders already in hand stretch into 2027. That is more visibility than most AI-exposed suppliers can claim. Orders hit a record $5.3B in the quarter, up 25% on the year and running ahead of sales, so the demand is booked rather than hoped for.

The lever to watch is the mix. AI is only about 13% of TE’s roughly $18.7B in annual sales today. The bull case is that this share climbs into the high teens or low twenties over the next two to three years, the point at which the slow car business stops dragging down the valuation. That share is the single number to track.

Valuation only means something in comparison, so here are three: peers now, TE against its own history, and the cash flows the market is discounting.

TE also looks cheap against itself. Its own trailing P/E sits at 21.9×, against a ten-year mean near 28× and a five-year range of 12.9× to 32.5×. So TE today is roughly 22% below its own long-run average. Amphenol has gone the other way: it re-rated up on AI and still trades at a premium to its own median near 30×. The gap is wide three ways at once, against Amphenol, against the AI-interconnect group, and against TE’s own past.

Putting the methods on one page, the implied price band by approach comes out as:

The cash flows tell the same story. At $214.50, a reverse-DCF says the market is discounting only about 4.4% free-cash-flow growth a year for ten years, on a 9% cost of capital and a 2.5% terminal rate. A company with that order book and 46% organic growth in its AI line is not a 4.4% grower, unless the car business drags everything down forever. Re-rate EV/EBITDA to 20×, still below the twin’s 25.6×, and the implied value is about $308, or +44%; at Amphenol parity it is about $399, or +86%. The bet is not on a boom. It is that the discount is too wide.

The honest way to bridge “should be worth more” and “$266” is to show the maths. The lever is not capacity. It is the exit multiple. AI revenue and the auto trajectory set the EPS, and the re-rating does the rest.

Bear

Base

Bull

Each fair value is the exit multiple applied to FY27 adjusted EPS, then discounted back about a year at a 9% cost of capital. That is why the base reads $266 rather than the naive $290 you get from 22× times $13.2. The discount keeps the base case honest. Read the table one way and the point jumps out: the swing factor is the exit multiple, not the EPS. Across all three cases the EPS barely moves, from $12.2 to $13.9, while the multiple swings from 14× to 28×. The value is made in the re-rating, which is also why the trade is easy to underprice.

This is a re-rating stock, so it trades on the multiple and on expectations as much as on the fundamentals. That makes the tape do counter-intuitive things. The cleanest example is that TE has, more than once, fallen on a quarter that was a clear beat with record orders. The reason was not the print. It was the bar. The market had already priced a strong quarter, so meeting it rather than clearing it was enough to trigger a sell-off.

The practical lesson on entry is to size and time around the expectations bar, not the print. A good quarter after a strong run can still correct, while a good-enough quarter on soft consensus is often where the multiple re-rates. The fundamentals here are solid. The work is in the timing.

Here is the tension we will not paper over. At a conservative 22× exit, the base-case upside (+24%) roughly matches the bear-case downside (−27%), so on the multiple alone the trade is close to a coin flip. It turns clearly asymmetric only once the exit multiple clears about 24×, which is still below both TE’s own history and Amphenol’s multiple. The call therefore rests on the re-rating, and the reverse-DCF is what tips the odds in its favour: at today’s price the market already assumes almost no growth.

The other thing we will not pretend away is that the gap to Amphenol is not random. Amphenol leads on speed, holds the larger Nvidia position, and earns its higher multiple for those reasons. The 43% discount is a real second-source discount, not a misprint. Our case is that the gap is too wide for what is, at the platform level, a very similar product. The bear case is that the gap is simply fair.

Bull

Bear

The one number we track from here is AI revenue as a share of the group. It is in the low teens today. When it clears roughly 15%, the auto drag stops setting the price, and the re-rating case stops being a forecast and starts being a fact.